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1. Static models for implementing photovoltaic panels characteristics under various environmental conditions using improved gradient-based optimizer

Author

Abd Elaziz, M, Almodfer, R, Ahmadianfar, I, Ibrahim, IA, Mudhsh, M, Abualigah, L, Lu, S, Abd El-Latif, AA, Yousri, D, Abd Elaziz, M, Almodfer, R, Ahmadianfar, I, Ibrahim, IA, Mudhsh, M, Abualigah, L, Lu, S, Abd El-Latif, AA, and Yousri, D

Abstract

An accurate definition of the photovoltaic (PV) models is an essential task to emulate and understand the physical behavior of the PV cell/panels. The highly used PV models are the static equivalent circuits, including single and double diode models. However, the accurate definition of the static models is mainly based on their estimated parameters. Proposing a reliable Optimization-based approached is a challenging aim. So, this paper proposes a novel and efficient optimizer to identify PV single and double diode models’ parameters for several PV modules using different sets of experimentally measured data. The developed method depends on improving the gradient-based optimization algorithm (GBO) using a new crossover operator to enhances agents’ diversity. Furthermore, a modified local escaping operator is applied to improve exploitation of GBO. The performance of the improvement GBO (IGBO) is evaluated using different experimental datasets for numerous PV modules under several operating conditions of temperature and radiation. The efficiency of IGBO is validated through a massive comparison with a set of recent state-of-the-art techniques. Reported results, fitting curves, and convergence curves provide proof for the efficiency of IGBO in providing high qualifies results with remarkable convergence speed.

Published
2022

3. REVOHPR: Relay-based Void Hole Prevention and Repair by Virtual Routing in Clustered Multi-AUV Underwater Wireless Sensor Network

Author

Soha Alhelaly, Ibrahim A. Elgendy, Chaaf A, Abdullah M. Iliyasu, Ammar Muthanna, Muthanna Msa, and Abd El-Latif Aa

Subjects
Computer science, business.industry, ComputerSystemsOrganization_COMPUTER-COMMUNICATIONNETWORKS, other, law.invention, Relay, law, Void (composites), Computer Science::Networking and Internet Architecture, Routing (electronic design automation), Cluster analysis, business, Underwater wireless sensor networks, Computer network
Abstract

Underwater Wireless Sensor Networks (UWSN) enables various oceanic applications which require effective packet transmission. In this case, sparse node distribution, dynamic network topology and inappropriate selection of relay nodes cause void holes. Addressing this problem, we present a Relay based Void Hole Prevention and Repair protocol (ReVOHPR) by multiple Autonomous Underwater Vehicles (AUV) for UWSN. ReVOHPR efficiently identifies and avoids void holes and trap relay nodes to avoid it. ReVOHPR adopts the following operations as Ocean Depth (levels) based Equal Cluster Formation, Dynamic Sleep Scheduling, Virtual Graph based Routing, and Relay Assisted Void Hole Repair. For energy efficient cluster forming, Entropy based Eligibility Ranking (E2R) is presented which elects stable cluster heads (CHs). Then, dynamic sleep scheduling is implemented Dynamic Kernel Kalman Filter (DK2F) algorithm in which Sleep and Active modes based on the nodes current status. Inter Cluster Routing is performed by maximum matching nodes which selects by Dual criteria and also data transmitted to AUV. Finally, void holes are detected and repair by Bi-Criteria Mayfly Optimization (BiCMO) algorithm. The BiCMO focuses on reducing the number of holes, data packet loss and maximizes Quality of Service (QoS) and energy efficiency of the networks. This protocol is timely deal with node failures in packet transmission via multi-hop routing. Simulation is implemented by NS3 (AquaSim module) simulator that evaluates the performance in network simulation for following metrics as average energy consumption, delay, packet delivery rate and throughput.

Published
2021

4. Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990–2015: findings from the Global Burden of Disease 2015 study

Author

Tehrani-Banihashemi, A, Moradi-Lakeh, M, Elbcheraoui, C, Charara, R, Khalil, I, Afshin, A, Collison, M, Daoud, F, Krohn, KJ, Chew, A, Cornaby, L, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kemmer, L, Kutz, M, Liu, P, Mirarefin, M, Nguyen, G, Wang, H, Zipkin, B, Abajobir, AA, Abouzeid, Marian, Abu-Rmeileh, NME, Ahmad Kiadaliri, A, Ahmed, MB, Aksut, B, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Ärnlöv, J, Asgedom, SW, Atey, TM, Awasthi, A, Bärnighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Bennett, DA, Berhe, DF, Biadgilign, S, Butt, ZA, Carapetis, JR, Castro, RE, Chitheer, AA, Davletov, K, Dharmaratne, SD, Djalalinia, S, Do, HP, Dubey, M, Ebrahimi, H, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, SM, Fischer, F, Gebrehiwot, SW, Gebrehiwot, TT, Gillum, RF, Gona, PN, Gupta, R, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hsairi, M, Jee, SH, Jonas, JB, Karimkhani, C, Kasaeian, A, Khader, YS, Khan, EA, Kim, D, Lal, DK, Larson, HJ, Latif, AA, Linn, S, Lotufo, PA, Lunevicius, R, Magdyabdelrazek, H, Majeed, A, Malekzadeh, R, Malta, DC, Meier, T, Memiah, P, Memish, ZA, Mendoza, W, Mensah, GA, Meretoja, A, Miller, TR, Mirrakhimov, EM, Mohammed, S, Nguyen, QL, Tehrani-Banihashemi, A, Moradi-Lakeh, M, Elbcheraoui, C, Charara, R, Khalil, I, Afshin, A, Collison, M, Daoud, F, Krohn, KJ, Chew, A, Cornaby, L, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kemmer, L, Kutz, M, Liu, P, Mirarefin, M, Nguyen, G, Wang, H, Zipkin, B, Abajobir, AA, Abouzeid, Marian, Abu-Rmeileh, NME, Ahmad Kiadaliri, A, Ahmed, MB, Aksut, B, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Ärnlöv, J, Asgedom, SW, Atey, TM, Awasthi, A, Bärnighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Bennett, DA, Berhe, DF, Biadgilign, S, Butt, ZA, Carapetis, JR, Castro, RE, Chitheer, AA, Davletov, K, Dharmaratne, SD, Djalalinia, S, Do, HP, Dubey, M, Ebrahimi, H, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, SM, Fischer, F, Gebrehiwot, SW, Gebrehiwot, TT, Gillum, RF, Gona, PN, Gupta, R, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hsairi, M, Jee, SH, Jonas, JB, Karimkhani, C, Kasaeian, A, Khader, YS, Khan, EA, Kim, D, Lal, DK, Larson, HJ, Latif, AA, Linn, S, Lotufo, PA, Lunevicius, R, Magdyabdelrazek, H, Majeed, A, Malekzadeh, R, Malta, DC, Meier, T, Memiah, P, Memish, ZA, Mendoza, W, Mensah, GA, Meretoja, A, Miller, TR, Mirrakhimov, EM, Mohammed, S, and Nguyen, QL

Abstract

Objectives: To report the burden of cardiovascular diseases (CVD) in the Eastern Mediterranean Region (EMR) during 1990–2015. Methods: We used the 2015 Global Burden of Disease study for estimates of mortality and disability-adjusted life years (DALYs) of different CVD in 22 countries of EMR. Results: A total of 1.4 million CVD deaths (95% UI: 1.3–1.5) occurred in 2015 in the EMR, with the highest number of deaths in Pakistan (465,116) and the lowest number of deaths in Qatar (723). The age-standardized DALY rate per 100,000 decreased from 10,080 in 1990 to 8606 in 2015 (14.6% decrease). Afghanistan had the highest age-standardized DALY rate of CVD in both 1990 and 2015. Kuwait and Qatar had the lowest age-standardized DALY rates of CVD in 1990 and 2015, respectively. High blood pressure, high total cholesterol, and high body mass index were the leading risk factors for CVD. Conclusions: The age-standardized DALY rates in the EMR are considerably higher than the global average. These findings call for a comprehensive approach to prevent and control the burden of CVD in the region.

Published
2018

5. Intentional injuries in the Eastern Mediterranean Region, 1990-2015: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Moradi-Lakeh, M, Charara, R, El Bcheraoui, C, Khalil, I, Afshin, A, Kassebaum, NJ, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Colombara, D, Graetz, N, Kutz, M, Wang, H, Abd-Allah, F, Abu-Raddad, LJ, Kiadaliri, AA, Ahmed, MB, Alam, K, Alghnam, S, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Anber, N, Anwari, P, Avila-Burgos, L, Awasthi, A, Barac, A, Barker-Collo, SL, Bedi, N, Bhutta, ZA, Borschmann, R, Boufous, S, Butt, ZA, Castaneda-Orjuela, CA, Dalal, K, Danawi, H, De Leo, D, Dharmaratne, SD, Djalalinia, S, Doyle, KE, Esteghamati, A, Faro, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gutierrez, RA, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Haro, JM, Hendrie, D, Hu, G, Jonas, JB, Kasaeian, A, Keiyoro, PN, Khader, YS, Khan, EA, Khubchandani, J, Kopec, JA, Larson, HJ, Latif, AA, Leshargie, CT, Lunevicius, R, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Memish, ZA, Meretoja, TJ, Miller, TR, Mohammed, S, Obermeyer, CM, Ogbo, FA, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiri, S, Salamati, P, Samy, AM, Sartorius, B, Seedat, S, Sepanlou, SG, Shaikh, MA, Sobaih, BHA, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, RomanTopor-Madry, Ukwaja, KN, Uthman, OA, Yaseri, M, NaohiroYonemoto, Younis, MZ, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Moradi-Lakeh, M, Charara, R, El Bcheraoui, C, Khalil, I, Afshin, A, Kassebaum, NJ, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Colombara, D, Graetz, N, Kutz, M, Wang, H, Abd-Allah, F, Abu-Raddad, LJ, Kiadaliri, AA, Ahmed, MB, Alam, K, Alghnam, S, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Anber, N, Anwari, P, Avila-Burgos, L, Awasthi, A, Barac, A, Barker-Collo, SL, Bedi, N, Bhutta, ZA, Borschmann, R, Boufous, S, Butt, ZA, Castaneda-Orjuela, CA, Dalal, K, Danawi, H, De Leo, D, Dharmaratne, SD, Djalalinia, S, Doyle, KE, Esteghamati, A, Faro, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gutierrez, RA, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Haro, JM, Hendrie, D, Hu, G, Jonas, JB, Kasaeian, A, Keiyoro, PN, Khader, YS, Khan, EA, Khubchandani, J, Kopec, JA, Larson, HJ, Latif, AA, Leshargie, CT, Lunevicius, R, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Memish, ZA, Meretoja, TJ, Miller, TR, Mohammed, S, Obermeyer, CM, Ogbo, FA, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiri, S, Salamati, P, Samy, AM, Sartorius, B, Seedat, S, Sepanlou, SG, Shaikh, MA, Sobaih, BHA, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, RomanTopor-Madry, Ukwaja, KN, Uthman, OA, Yaseri, M, NaohiroYonemoto, Younis, MZ, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, and Murray, CJL

Abstract

OBJECTIVES: We used GBD 2015 findings to measure the burden of intentional injuries in the Eastern Mediterranean Region (EMR) between 1990 and 2015. METHODS: The Global Burden of Disease (GBD) study defines intentional injuries as a combination of self-harm (including suicide), interpersonal violence, collective violence (war), and legal intervention. We estimated number of deaths, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life years (DALYs) for each type of intentional injuries. RESULTS: In 2015, 28,695 individuals (95% UI: 25,474-37,832) died from self-harm, 35,626 (95% UI: 20,947-41,857) from interpersonal violence, and 143,858 (95% UI: 63,554-223,092) from collective violence and legal interventions. In 2015, collective violence and legal intervention was the fifth-leading cause of DALYs in the EMR and the leading cause in Syria, Yemen, Iraq, Afghanistan, and Libya; they account for 49.7% of total DALYs in Syria. CONCLUSIONS: Our findings call for increased efforts to stabilize the region and assist in rebuilding the health systems, as well as increasing transparency and employing preventive strategies to reduce self-harm and interpersonal injuries.

Published
2018

6. Maternal mortality and morbidity burden in the Eastern Mediterranean Region: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Khalil, I, Collison, M, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Chew, A, Daoud, F, Krohn, KJ, Colombara, D, Ehrenkranz, R, Kutz, M, Wang, H, Abajobir, AA, Abd-Allah, F, Abraha, HN, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Al Lami, FH, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Alkaabi, JM, Al-Maskari, F, Al-Raddadi, R, Altirkawi, KA, Anber, N, Ansari, H, Asayesh, H, Asghar, RJ, Atey, TM, Ayele, TA, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Baune, BT, Bazargan-Hejazi, S, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Beyene, AS, Bhutta, ZA, Boneya, DJ, Borschmann, R, Breitborde, NJK, Butt, ZA, Catala-Lopez, F, Ciobanu, LG, Danawi, H, Deribew, A, Dharmaratne, SD, Doyle, KE, Endries, AY, Faraon, EJA, Faro, A, Farvid, MS, Fekadu, W, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giref, AZ, Gishu, MD, Goulart, AC, Habtewold, TD, Hamadeh, RR, Hambisa, MT, Hamidi, S, Maria Haro, J, Hassanvand, MS, Horita, N, Hsairi, M, Huang, H, Husseini, A, Jakovljevic, MB, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khoja, ATA, Khosravi, A, Khubchandani, J, Kim, D, Kim, YJ, Kokubo, Y, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lee, PH, Leshargie, CT, Leung, R, Lo, L-T, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Martinez-Raga, J, Farid, HM, Mazidi, M, McGrath, JJ, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Mensah, GA, Mezgebe, HB, Miller, TR, Mitchell, PB, Mohammadi, A, Mohammed, S, Obermeyer, CM, Ogbo, FA, Palomares Castillo, E, Papachristou, C, Patten, SB, Patton, GC, Pereira, DM, Pervaiz, A, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiabadi, M, Safiri, S, Sagar, R, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Saylan, MI, Seedat, S, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Santos Silva, DA, Singh, JA, Sobaih, BHA, Sreeramareddy, CT, Stein, DJ, Abdulkader, RS, Sykes, BL, Tabares-Seisdedos, R, Sufiyan, M, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Topor-Madry, R, Ukwaja, KN, Uthman, OA, Vollset, SE, Wakayo, T, Wang, Y-P, Werdecker, A, Westerman, R, Workicho, A, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Kassebaum, NJ, Murray, CJL, Mokdad, AH, Khalil, I, Collison, M, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Chew, A, Daoud, F, Krohn, KJ, Colombara, D, Ehrenkranz, R, Kutz, M, Wang, H, Abajobir, AA, Abd-Allah, F, Abraha, HN, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Al Lami, FH, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Alkaabi, JM, Al-Maskari, F, Al-Raddadi, R, Altirkawi, KA, Anber, N, Ansari, H, Asayesh, H, Asghar, RJ, Atey, TM, Ayele, TA, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Baune, BT, Bazargan-Hejazi, S, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Beyene, AS, Bhutta, ZA, Boneya, DJ, Borschmann, R, Breitborde, NJK, Butt, ZA, Catala-Lopez, F, Ciobanu, LG, Danawi, H, Deribew, A, Dharmaratne, SD, Doyle, KE, Endries, AY, Faraon, EJA, Faro, A, Farvid, MS, Fekadu, W, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giref, AZ, Gishu, MD, Goulart, AC, Habtewold, TD, Hamadeh, RR, Hambisa, MT, Hamidi, S, Maria Haro, J, Hassanvand, MS, Horita, N, Hsairi, M, Huang, H, Husseini, A, Jakovljevic, MB, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khoja, ATA, Khosravi, A, Khubchandani, J, Kim, D, Kim, YJ, Kokubo, Y, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lee, PH, Leshargie, CT, Leung, R, Lo, L-T, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Martinez-Raga, J, Farid, HM, Mazidi, M, McGrath, JJ, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Mensah, GA, Mezgebe, HB, Miller, TR, Mitchell, PB, Mohammadi, A, Mohammed, S, Obermeyer, CM, Ogbo, FA, Palomares Castillo, E, Papachristou, C, Patten, SB, Patton, GC, Pereira, DM, Pervaiz, A, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiabadi, M, Safiri, S, Sagar, R, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Saylan, MI, Seedat, S, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Santos Silva, DA, Singh, JA, Sobaih, BHA, Sreeramareddy, CT, Stein, DJ, Abdulkader, RS, Sykes, BL, Tabares-Seisdedos, R, Sufiyan, M, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Topor-Madry, R, Ukwaja, KN, Uthman, OA, Vollset, SE, Wakayo, T, Wang, Y-P, Werdecker, A, Westerman, R, Workicho, A, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Kassebaum, NJ, and Murray, CJL

Abstract

OBJECTIVES: Assessing the burden of maternal mortality is important for tracking progress and identifying public health gaps. This paper provides an overview of the burden of maternal mortality in the Eastern Mediterranean Region (EMR) by underlying cause and age from 1990 to 2015. METHODS: We used the results of the Global Burden of Disease 2015 study to explore maternal mortality in the EMR countries. RESULTS: The maternal mortality ratio in the EMR decreased 16.3% from 283 (241-328) maternal deaths per 100,000 live births in 1990 to 237 (188-293) in 2015. Maternal mortality ratio was strongly correlated with socio-demographic status, where the lowest-income countries contributed the most to the burden of maternal mortality in the region. CONCLUSION: Progress in reducing maternal mortality in the EMR has accelerated in the past 15 years, but the burden remains high. Coordinated and rigorous efforts are needed to make sure that adequate and timely services and interventions are available for women at each stage of reproductive life.

Published
2018

7. Burden of vision loss in the Eastern Mediterranean region, 1990-2015: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Safi, S, Ahmadieh, H, Katibeh, M, Yaseri, M, Ramezani, A, Shahraz, S, Moradi-Lakeh, M, Khalil, I, El Bcheraoui, C, Collison, M, Chew, A, Daoud, F, Krohn, KJ, Rankin, Z, Afshin, A, Kassebaum, NJ, Olsen, HE, Stanaway, JD, Wang, H, Wilson, K, Yitayih, G, Al-Eyadhy, A, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Anber, N, Ansari, H, Anwari, P, Asayesh, H, Asgedom, SW, Atey, TM, Bacha, U, Barac, A, Bedi, N, Butt, ZA, Chitheer, AA, Djalalinia, S, Huyen, DP, Eshrati, B, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Hamadeh, RR, Hamidi, S, Higazi, TB, Hsairi, M, Jimenez-Corona, A, John, D, Jonas, JB, Kasaeian, A, Saleh, Y, Khan, EA, Larson, HJ, Latif, AA, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, McAlinden, C, Memish, ZA, Miller, TR, Mohammadi, S-F, Nangia, V, Cuong, TN, Quyen, LN, Ogbo, FA, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roshandel, G, Safdarian, M, Safiri, S, Salamati, P, Samy, AM, Sartorius, B, Sepanlou, SG, Shaikh, MA, Skiadaresi, E, Sobaih, BHA, Abdulkader, RS, Taylor, HR, Tehrani-Banihashemi, A, Temsah, M-H, Topor-Madry, R, Xuan, B, Tsilimbaris, M, Ukwaja, KN, Uthman, OA, Wakayo, T, Yonemoto, N, Younis, MZ, Zaki, MES, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Safi, S, Ahmadieh, H, Katibeh, M, Yaseri, M, Ramezani, A, Shahraz, S, Moradi-Lakeh, M, Khalil, I, El Bcheraoui, C, Collison, M, Chew, A, Daoud, F, Krohn, KJ, Rankin, Z, Afshin, A, Kassebaum, NJ, Olsen, HE, Stanaway, JD, Wang, H, Wilson, K, Yitayih, G, Al-Eyadhy, A, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Anber, N, Ansari, H, Anwari, P, Asayesh, H, Asgedom, SW, Atey, TM, Bacha, U, Barac, A, Bedi, N, Butt, ZA, Chitheer, AA, Djalalinia, S, Huyen, DP, Eshrati, B, Farvid, MS, Farzadfar, F, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Hamadeh, RR, Hamidi, S, Higazi, TB, Hsairi, M, Jimenez-Corona, A, John, D, Jonas, JB, Kasaeian, A, Saleh, Y, Khan, EA, Larson, HJ, Latif, AA, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, McAlinden, C, Memish, ZA, Miller, TR, Mohammadi, S-F, Nangia, V, Cuong, TN, Quyen, LN, Ogbo, FA, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roshandel, G, Safdarian, M, Safiri, S, Salamati, P, Samy, AM, Sartorius, B, Sepanlou, SG, Shaikh, MA, Skiadaresi, E, Sobaih, BHA, Abdulkader, RS, Taylor, HR, Tehrani-Banihashemi, A, Temsah, M-H, Topor-Madry, R, Xuan, B, Tsilimbaris, M, Ukwaja, KN, Uthman, OA, Wakayo, T, Yonemoto, N, Younis, MZ, Zaki, MES, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, and Murray, CJL

Abstract

OBJECTIVES: To report the estimated trend in prevalence and years lived with disability (YLDs) due to vision loss (VL) in the Eastern Mediterranean region (EMR) from 1990 to 2015. METHODS: The estimated trends in age-standardized prevalence and the YLDs rate due to VL in 22 EMR countries were extracted from the Global Burden of Disease (GBD) 2015 study. The association of Socio-demographic Index (SDI) with changes in prevalence and YLDs of VL was evaluated using a multilevel mixed model. RESULTS: The age-standardized prevalence of VL in the EMR was 18.2% in 1990 and 15.5% in 2015. The total age-standardized YLDs rate attributed to all-cause VL in EMR was 536.9 per 100,000 population in 1990 and 482.3 per 100,000 population in 2015. For each 0.1 unit increase in SDI, the age-standardized prevalence and YLDs rate of VL showed a reduction of 1.5% (p < 0.001) and 23.9 per 100,000 population (p < 0.001), respectively. CONCLUSIONS: The burden of VL is high in the EMR; however, it shows a descending trend over the past 25 years. EMR countries need to establish comprehensive eye care programs in their health care systems.

Published
2018

8. The burden of mental disorders in the Eastern Mediterranean region, 1990-2015: findings from the global burden of disease 2015 study

Author

Mokdad, AH, Charara, R, El Bcheraoui, C, Khalil, I, Moradi-Lakeh, M, Afshin, A, Kassebaum, NJ, Collison, M, Krohn, KJ, Chew, A, Daoud, F, Charlson, FJ, Colombara, D, Degenhardt, L, Ehrenkranz, R, Erskine, HE, Ferrari, AJ, Kutz, M, Leung, J, Santomauro, D, Wang, H, Whiteford, HA, Abajobir, AA, Abd-Allah, F, Abraha, HN, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Yimam, K, Beshir, M, Al Lami, FH, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Alkaabi, JM, Al-Maskari, F, Al-Raddadi, R, Altirkawi, KA, Anber, N, Ansari, H, Asayesh, H, Asghar, RJ, Atey, TM, Ayele, TA, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Baune, BT, Bazargan-Hejazi, S, Drew, CR, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Beyene, AS, Bhutta, ZA, Boneya, DJ, Borschmann, R, Breitborde, NJK, Butt, ZA, Catala-Lopez, F, Ciobanu, LG, Danawi, H, Deribew, A, Dharmaratne, SD, Doyle, KE, Endries, AY, Faraon, EJA, Faro, A, Farvid, MS, Fekadu, W, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giref, AZ, Gishu, MD, Carvalho, A, Habtewold, TD, Hamadeh, RR, Hambisa, MT, Hamidi, S, Haro, JM, Hassanvand, MS, Horita, N, Hsairi, M, Huang, H, Husseini, A, Jakovljevic, MB, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khoja, ATA, Khosravi, A, Khubchandani, J, Kim, D, Kim, YJ, Kokubo, Y, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lee, PH, Leshargie, CT, Leung, R, Lo, L-T, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Martinez-Raga, J, Farid, HM, Mazidi, M, McGrath, JJ, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Mezgebe, HB, Miller, TR, Mitchell, PB, Mohammadi, A, Mohammed, S, Obermeyer, CM, Ogbo, FA, Castillo, EP, Papachristou, C, Patten, SB, Patton, GC, Pervaiz, A, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiabadi, M, Safiri, S, Sagar, R, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Saylan, MI, Seedat, S, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Silva, DAS, Singh, JA, Sobaih, BHA, Stein, DJ, Abdulkader, RS, Sykes, BL, Tabares-Seisdedos, R, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Topor-Madry, R, Ukwaja, KN, Uthman, OA, Vollset, SE, Wakayo, T, Wang, Y-P, Werdecker, A, Westerman, R, Workicho, A, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Charara, R, El Bcheraoui, C, Khalil, I, Moradi-Lakeh, M, Afshin, A, Kassebaum, NJ, Collison, M, Krohn, KJ, Chew, A, Daoud, F, Charlson, FJ, Colombara, D, Degenhardt, L, Ehrenkranz, R, Erskine, HE, Ferrari, AJ, Kutz, M, Leung, J, Santomauro, D, Wang, H, Whiteford, HA, Abajobir, AA, Abd-Allah, F, Abraha, HN, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Yimam, K, Beshir, M, Al Lami, FH, Alam, K, Alasfoor, D, Alizadeh-Navaei, R, Alkaabi, JM, Al-Maskari, F, Al-Raddadi, R, Altirkawi, KA, Anber, N, Ansari, H, Asayesh, H, Asghar, RJ, Atey, TM, Ayele, TA, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Baune, BT, Bazargan-Hejazi, S, Drew, CR, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Beyene, AS, Bhutta, ZA, Boneya, DJ, Borschmann, R, Breitborde, NJK, Butt, ZA, Catala-Lopez, F, Ciobanu, LG, Danawi, H, Deribew, A, Dharmaratne, SD, Doyle, KE, Endries, AY, Faraon, EJA, Faro, A, Farvid, MS, Fekadu, W, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giref, AZ, Gishu, MD, Carvalho, A, Habtewold, TD, Hamadeh, RR, Hambisa, MT, Hamidi, S, Haro, JM, Hassanvand, MS, Horita, N, Hsairi, M, Huang, H, Husseini, A, Jakovljevic, MB, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khoja, ATA, Khosravi, A, Khubchandani, J, Kim, D, Kim, YJ, Kokubo, Y, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lee, PH, Leshargie, CT, Leung, R, Lo, L-T, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Martinez-Raga, J, Farid, HM, Mazidi, M, McGrath, JJ, Memish, ZA, Mendoza, W, Mengesha, MM, Mengistie, MA, Mezgebe, HB, Miller, TR, Mitchell, PB, Mohammadi, A, Mohammed, S, Obermeyer, CM, Ogbo, FA, Castillo, EP, Papachristou, C, Patten, SB, Patton, GC, Pervaiz, A, Phillips, MR, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roshandel, G, Safdarian, M, Safiabadi, M, Safiri, S, Sagar, R, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Saylan, MI, Seedat, S, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Silva, DAS, Singh, JA, Sobaih, BHA, Stein, DJ, Abdulkader, RS, Sykes, BL, Tabares-Seisdedos, R, Tabb, KM, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Topor-Madry, R, Ukwaja, KN, Uthman, OA, Vollset, SE, Wakayo, T, Wang, Y-P, Werdecker, A, Westerman, R, Workicho, A, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, and Murray, CJL

Abstract

OBJECTIVES: Mental disorders are among the leading causes of nonfatal burden of disease globally. METHODS: We used the global burden of diseases, injuries, and risk factors study 2015 to examine the burden of mental disorders in the Eastern Mediterranean region (EMR). We defined mental disorders according to criteria proposed in the diagnostic and statistical manual of mental disorders IV and the 10th International Classification of Diseases. RESULTS: Mental disorders contributed to 4.7% (95% uncertainty interval (UI) 3.7-5.6%) of total disability-adjusted life-years (DALYs), ranking as the ninth leading cause of disease burden. Depressive disorders and anxiety disorders were the third and ninth leading causes of nonfatal burden, respectively. Almost all countries in the EMR had higher age-standardized mental disorder DALYs rates compared to the global level, and in half of the EMR countries, observed mental disorder rates exceeded the expected values. CONCLUSIONS: The burden of mental disorders in the EMR is higher than global levels, particularly for women. To properly address this burden, EMR governments should implement nationwide quality epidemiological surveillance of mental disorders and provide adequate prevention and treatment services.

Published
2018

9. Burden of lower respiratory infections in the Eastern Mediterranean Region between 1990 and 2015: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Moradi-Lakeh, M, El Bcheraoui, C, Charara, R, Khalil, I, Afshin, A, Kassebaum, NJ, Collison, M, Daoud, F, Chew, A, Krohn, KJ, Colombara, D, Ehrenkranz, R, Foreman, KJ, Frostad, J, Godwin, WW, Kutz, M, Rao, PC, Reiner, R, Troeger, C, Wang, H, Abajobir, AA, Abbas, KM, Abera, SF, Abu-Raddad, LJ, Adane, K, Kiadaliri, AA, Ahmadi, A, Beshir, M, Al-Eyadhy, A, Alam, K, Alam, N, Alasfoor, D, Alizadeh-Navaei, R, Al-Maskari, F, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Anber, N, Ansari, H, Antonio, CAT, Anwari, P, Asayesh, H, Asgedom, SW, Atey, TM, Arthur, EFG, Bacha, U, Barac, A, Bazargan-Hejazi, S, Drew, CR, Geffen, D, Bedi, N, Bhutta, ZA, Michael, B, Butt, ZA, Castaneda-Orjuela, CA, Danawi, H, Djalalinia, S, Endries, AY, Eshrati, B, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Garcia-Basteiro, AL, Gebrehiwot, KT, Gebrehiwot, TT, Hailu, GB, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hassanvand, MS, Hedayati, MT, Horita, N, Husseini, A, Spencer, LJ, Javanbakht, M, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Khoja, ATA, Khubchandani, J, Kim, YJ, Kissoon, N, Larson, HJ, Latif, AA, Leshargie, CT, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Farid, HM, Mehari, A, Memish, ZA, Mengistu, DT, Mensah, GA, Mezgebe, HB, Nakamura, S, Oren, E, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Vafa, R-M, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roba, HS, Roshandel, G, Safdarian, M, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Shigematsu, M, Singh, JA, Sufiyan, MB, Tehrani-Banihashemi, A, Temsah, M-H, Topor-Madry, R, Uthman, OA, Vollset, SE, Wakayo, T, Werdecker, A, Wijeratne, T, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Zaki, MES, Jumaan, AO, Vos, T, Naghavi, M, Hay, SI, Murray, CJL, Mokdad, AH, Moradi-Lakeh, M, El Bcheraoui, C, Charara, R, Khalil, I, Afshin, A, Kassebaum, NJ, Collison, M, Daoud, F, Chew, A, Krohn, KJ, Colombara, D, Ehrenkranz, R, Foreman, KJ, Frostad, J, Godwin, WW, Kutz, M, Rao, PC, Reiner, R, Troeger, C, Wang, H, Abajobir, AA, Abbas, KM, Abera, SF, Abu-Raddad, LJ, Adane, K, Kiadaliri, AA, Ahmadi, A, Beshir, M, Al-Eyadhy, A, Alam, K, Alam, N, Alasfoor, D, Alizadeh-Navaei, R, Al-Maskari, F, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Anber, N, Ansari, H, Antonio, CAT, Anwari, P, Asayesh, H, Asgedom, SW, Atey, TM, Arthur, EFG, Bacha, U, Barac, A, Bazargan-Hejazi, S, Drew, CR, Geffen, D, Bedi, N, Bhutta, ZA, Michael, B, Butt, ZA, Castaneda-Orjuela, CA, Danawi, H, Djalalinia, S, Endries, AY, Eshrati, B, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Garcia-Basteiro, AL, Gebrehiwot, KT, Gebrehiwot, TT, Hailu, GB, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hassanvand, MS, Hedayati, MT, Horita, N, Husseini, A, Spencer, LJ, Javanbakht, M, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Khoja, ATA, Khubchandani, J, Kim, YJ, Kissoon, N, Larson, HJ, Latif, AA, Leshargie, CT, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Farid, HM, Mehari, A, Memish, ZA, Mengistu, DT, Mensah, GA, Mezgebe, HB, Nakamura, S, Oren, E, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Vafa, R-M, Rai, RK, Rawaf, DL, Rawaf, S, Refaat, AH, Rezaei, S, Rezai, MS, Roba, HS, Roshandel, G, Safdarian, M, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shamsizadeh, M, Shigematsu, M, Singh, JA, Sufiyan, MB, Tehrani-Banihashemi, A, Temsah, M-H, Topor-Madry, R, Uthman, OA, Vollset, SE, Wakayo, T, Werdecker, A, Wijeratne, T, Yaghoubi, M, Yimam, HH, Yonemoto, N, Younis, MZ, Zaki, MES, Jumaan, AO, Vos, T, Naghavi, M, Hay, SI, and Murray, CJL

Abstract

OBJECTIVES: We used data from the Global Burden of Disease 2015 study (GBD) to calculate the burden of lower respiratory infections (LRIs) in the 22 countries of the Eastern Mediterranean Region (EMR) from 1990 to 2015. METHODS: We conducted a systematic analysis of mortality and morbidity data for LRI and its specific etiologic factors, including pneumococcus, Haemophilus influenzae type b, Respiratory syncytial virus, and influenza virus. We used modeling methods to estimate incidence, deaths, and disability-adjusted life-years (DALYs). We calculated burden attributable to known risk factors for LRI. RESULTS: In 2015, LRIs were the fourth-leading cause of DALYs, causing 11,098,243 (95% UI 9,857,095-12,396,566) DALYs and 191,114 (95% UI 170,934-210,705) deaths. The LRI DALY rates were higher than global estimates in 2015. The highest and lowest age-standardized rates of DALYs were observed in Somalia and Lebanon, respectively. Undernutrition in childhood and ambient particulate matter air pollution in the elderly were the main risk factors. CONCLUSIONS: Our findings call for public health strategies to reduce the level of risk factors in each age group, especially vulnerable child and elderly populations.

Published
2018

10. Burden of cancer in the Eastern Mediterranean Region, 2005-2015: findings from the Global Burden of Disease 2015 Study

Author

Fitzmaurice, C, Alsharif, U, El Bcheraoui, C, Khalil, I, Charara, R, Moradi-Lakeh, M, Afshin, A, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Dicker, D, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kutz, M, Wang, H, Abyu, GY, Adedeji, IA, Kiadaliri, AA, Ahmed, MB, Al-Eyadhy, A, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Alvis-Guzman, N, Amini, E, Anber, N, Anwari, P, Artaman, A, Asgedom, SW, Atey, TM, Awasthi, A, Saleem, HOB, Bacha, U, Barac, A, Bedi, N, Bhutta, ZA, Butt, ZA, Castaneda-Orjuela, CA, Chitheer, AA, Danawi, H, das Neves, J, Davitoiu, DV, Dey, S, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Dubey, M, Ebrahimi, H, Ekwueme, DU, Endries, AY, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gopalani, SV, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hareri, HA, Hay, RJ, Horita, N, Hsairi, M, Jakovljevic, MB, Jonas, JB, Kasaeian, A, Kassaw, NA, Khader, YS, Khan, EA, Khan, G, Kim, D, Kinfu, Y, Larson, HJ, Latif, AA, Linn, S, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Malta, DC, Markos, D, Memiah, P, Memish, ZA, Mendoza, W, Meretoja, TJ, Miller, TR, Mohammed, S, Nangia, V, Quyen, LN, Trang, HN, Ogbo, FA, Mahesh, PA, Park, E-K, Patel, T, Pereira, DM, Pishgar, F, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, S, Renzaho, AMN, Rezaei, S, Roba, KT, Roshandel, G, Safdarian, M, Safi, S, Safiri, S, Salamati, P, Samy, AM, Sanabria, JR, Milicevic, MMS, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shrime, MG, Stathopoulou, V, Sufiyan, MB, Abdulkader, RS, Tabares-Seisdedos, R, Tehrani-Banihashemi, A, Tekelab, T, Temsah, M-H, Tran, BX, Ukwaja, KN, Uthman, OA, Vlassov, VV, Vollset, SE, Wakayo, T, Weiderpass, E, Werdecker, A, Yaghoubi, M, Yaseri, M, Yimam, HH, Yonemoto, N, Zaki, MES, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Fitzmaurice, C, Alsharif, U, El Bcheraoui, C, Khalil, I, Charara, R, Moradi-Lakeh, M, Afshin, A, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Dicker, D, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kutz, M, Wang, H, Abyu, GY, Adedeji, IA, Kiadaliri, AA, Ahmed, MB, Al-Eyadhy, A, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Alvis-Guzman, N, Amini, E, Anber, N, Anwari, P, Artaman, A, Asgedom, SW, Atey, TM, Awasthi, A, Saleem, HOB, Bacha, U, Barac, A, Bedi, N, Bhutta, ZA, Butt, ZA, Castaneda-Orjuela, CA, Chitheer, AA, Danawi, H, das Neves, J, Davitoiu, DV, Dey, S, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Dubey, M, Ebrahimi, H, Ekwueme, DU, Endries, AY, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gopalani, SV, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hareri, HA, Hay, RJ, Horita, N, Hsairi, M, Jakovljevic, MB, Jonas, JB, Kasaeian, A, Kassaw, NA, Khader, YS, Khan, EA, Khan, G, Kim, D, Kinfu, Y, Larson, HJ, Latif, AA, Linn, S, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Malta, DC, Markos, D, Memiah, P, Memish, ZA, Mendoza, W, Meretoja, TJ, Miller, TR, Mohammed, S, Nangia, V, Quyen, LN, Trang, HN, Ogbo, FA, Mahesh, PA, Park, E-K, Patel, T, Pereira, DM, Pishgar, F, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, S, Renzaho, AMN, Rezaei, S, Roba, KT, Roshandel, G, Safdarian, M, Safi, S, Safiri, S, Salamati, P, Samy, AM, Sanabria, JR, Milicevic, MMS, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shrime, MG, Stathopoulou, V, Sufiyan, MB, Abdulkader, RS, Tabares-Seisdedos, R, Tehrani-Banihashemi, A, Tekelab, T, Temsah, M-H, Tran, BX, Ukwaja, KN, Uthman, OA, Vlassov, VV, Vollset, SE, Wakayo, T, Weiderpass, E, Werdecker, A, Yaghoubi, M, Yaseri, M, Yimam, HH, Yonemoto, N, Zaki, MES, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, and Mokdad, AH

Abstract

OBJECTIVES: To estimate incidence, mortality, and disability-adjusted life years (DALYs) caused by cancer in the Eastern Mediterranean Region (EMR) between 2005 and 2015. METHODS: Vital registration system and cancer registry data from the EMR region were analyzed for 29 cancer groups in 22 EMR countries using the Global Burden of Disease Study 2015 methodology. RESULTS: In 2015, cancer was responsible for 9.4% of all deaths and 5.1% of all DALYs. It accounted for 722,646 new cases, 379,093 deaths, and 11.7 million DALYs. Between 2005 and 2015, incident cases increased by 46%, deaths by 33%, and DALYs by 31%. The increase in cancer incidence was largely driven by population growth and population aging. Breast cancer, lung cancer, and leukemia were the most common cancers, while lung, breast, and stomach cancers caused most cancer deaths. CONCLUSIONS: Cancer is responsible for a substantial disease burden in the EMR, which is increasing. There is an urgent need to expand cancer prevention, screening, and awareness programs in EMR countries as well as to improve diagnosis, treatment, and palliative care services.

Published
2018

11. Neonatal, infant, and under-5 mortality and morbidity burden in the Eastern Mediterranean region: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Khalil, I, Collison, M, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Krohn, KJ, Daoud, F, Chew, A, Kassebaum, NJ, Colombara, D, Cornaby, L, Ehrenkranz, R, Foreman, KJ, Fraser, M, Frostad, J, Kemmer, L, Kulikoff, XR, Kutz, M, Kyu, HH, Liu, P, Mikesell, J, Nguyen, G, Rao, PC, Silpakit, N, Sligar, A, Smith, A, Stanaway, JD, Arnlov, J, Abate, KH, Kiadaliri, AA, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Alraddadi, R, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Ansari, H, Antonio, CAT, Anwari, P, Artaman, A, Asayesh, H, Asgedom, SW, Azzopardi, P, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Beghi, E, Bennett, DA, Bhutta, ZA, Bisanzio, D, Castaneda-Orjuela, CA, Estanislao Castro, R, Danawi, H, Deribe, K, Deribew, A, Jarlais, DCD, deVeber, GA, Dey, S, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giussani, G, Gona, PN, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hoy, DG, Hu, G, John, D, Jonas, JB, Karimi, SM, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Kim, D, Kim, YJ, Kinfu, Y, Larson, HJ, Latif, AA, Leasher, JL, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Memish, ZA, Mendoza, W, Mezgebe, HB, Miller, TR, Monasta, L, Quyen, LN, Obermeyer, CM, Ortiz, A, Papachristou, C, Park, E-K, Pereira, CC, Petzold, M, Pereira, DM, Phillips, MR, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Rezai, MS, Ronfani, L, Roshandel, G, Ruhago, GM, Safdarian, M, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Sanabria, JR, Sartorius, B, Schwebel, DC, Seedat, S, Sepanlou, SG, Setegn, T, Shaheen, A, Shaikh, MA, Shamsizadeh, M, Shiri, R, Skirbekk, V, Sobaih, BHA, Sreeramareddy, CT, Stathopoulou, V, Abdulkader, RS, Tehrani-Banihashemi, A, Temsah, M-H, Thakur, AJS, Thomson, AJ, Tran, BX, Truelsen, T, Ukwaja, KN, Uthman, OA, Vasankari, T, Vlassov, VV, Weiderpass, E, Weintraub, RG, Werdecker, A, Yaghoubi, M, Yaseri, M, Yonemoto, N, Younis, MZ, Yu, C, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Wang, H, Murray, CJL, Mokdad, AH, Khalil, I, Collison, M, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Krohn, KJ, Daoud, F, Chew, A, Kassebaum, NJ, Colombara, D, Cornaby, L, Ehrenkranz, R, Foreman, KJ, Fraser, M, Frostad, J, Kemmer, L, Kulikoff, XR, Kutz, M, Kyu, HH, Liu, P, Mikesell, J, Nguyen, G, Rao, PC, Silpakit, N, Sligar, A, Smith, A, Stanaway, JD, Arnlov, J, Abate, KH, Kiadaliri, AA, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Alraddadi, R, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Ansari, H, Antonio, CAT, Anwari, P, Artaman, A, Asayesh, H, Asgedom, SW, Azzopardi, P, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Beghi, E, Bennett, DA, Bhutta, ZA, Bisanzio, D, Castaneda-Orjuela, CA, Estanislao Castro, R, Danawi, H, Deribe, K, Deribew, A, Jarlais, DCD, deVeber, GA, Dey, S, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Giussani, G, Gona, PN, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hoy, DG, Hu, G, John, D, Jonas, JB, Karimi, SM, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Kim, D, Kim, YJ, Kinfu, Y, Larson, HJ, Latif, AA, Leasher, JL, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majeed, A, Malekzadeh, R, Memish, ZA, Mendoza, W, Mezgebe, HB, Miller, TR, Monasta, L, Quyen, LN, Obermeyer, CM, Ortiz, A, Papachristou, C, Park, E-K, Pereira, CC, Petzold, M, Pereira, DM, Phillips, MR, Pourmalek, F, Qorbani, M, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Rezai, MS, Ronfani, L, Roshandel, G, Ruhago, GM, Safdarian, M, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Sanabria, JR, Sartorius, B, Schwebel, DC, Seedat, S, Sepanlou, SG, Setegn, T, Shaheen, A, Shaikh, MA, Shamsizadeh, M, Shiri, R, Skirbekk, V, Sobaih, BHA, Sreeramareddy, CT, Stathopoulou, V, Abdulkader, RS, Tehrani-Banihashemi, A, Temsah, M-H, Thakur, AJS, Thomson, AJ, Tran, BX, Truelsen, T, Ukwaja, KN, Uthman, OA, Vasankari, T, Vlassov, VV, Weiderpass, E, Weintraub, RG, Werdecker, A, Yaghoubi, M, Yaseri, M, Yonemoto, N, Younis, MZ, Yu, C, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Wang, H, and Murray, CJL

Abstract

OBJECTIVES: Although substantial reductions in under-5 mortality have been observed during the past 35 years, progress in the Eastern Mediterranean Region (EMR) has been uneven. This paper provides an overview of child mortality and morbidity in the EMR based on the Global Burden of Disease (GBD) study. METHODS: We used GBD 2015 study results to explore under-5 mortality and morbidity in EMR countries. RESULTS: In 2015, 755,844 (95% uncertainty interval (UI) 712,064-801,565) children under 5 died in the EMR. In the early neonatal category, deaths in the EMR decreased by 22.4%, compared to 42.4% globally. The rate of years of life lost per 100,000 population under 5 decreased 54.38% from 177,537 (173,812-181,463) in 1990 to 80,985 (76,308-85,876) in 2015; the rate of years lived with disability decreased by 0.57% in the EMR compared to 9.97% globally. CONCLUSIONS: Our findings call for accelerated action to decrease child morbidity and mortality in the EMR. Governments and organizations should coordinate efforts to address this burden. Political commitment is needed to ensure that child health receives the resources needed to end preventable deaths.

Published
2018

12. Burden of cardiovascular diseases in the Eastern Mediterranean Region, 1990-2015: findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Tehrani-Banihashemi, A, Moradi-Lakeh, M, El Bcheraoui, C, Charara, R, Khalil, I, Afshin, A, Collison, M, Daoud, F, Krohn, KJ, Chew, A, Cornaby, L, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kemmer, L, Kutz, M, Liu, P, Mirarefin, M, Nguyen, G, Wang, H, Zipkin, B, Abajobir, AA, Abouzeid, M, Abu-Rmeileh, NME, Kiadaliri, AA, Ahmed, MB, Aksut, B, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Arnlov, J, Asgedom, SW, Atey, TM, Awasthi, A, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Bennett, DA, Berhe, DF, Biadgilign, S, Butt, ZA, Carapetis, JR, Estanislao Castro, R, Chitheer, AA, Davletov, K, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Dubey, M, Ebrahimi, H, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, SW, Gebrehiwot, TT, Gillum, RF, Gona, PN, Gupta, R, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hsairi, M, Jee, SH, Jonas, JB, Karimkhani, C, Kasaeian, A, Khader, YS, Khan, EA, Kim, D, Lal, DK, Larson, HJ, Latif, AA, Linn, S, Lotufo, PA, Lunevicius, R, Abd El Razek, HM, Majeed, A, Malekzadeh, R, Malta, DC, Meier, T, Memiah, P, Memish, ZA, Mendoza, W, Mensah, GA, Meretoja, A, Miller, TR, Mirrakhimov, EM, Mohammed, S, Quyen, LN, Vuong, MN, Pearson-Stuttard, J, Pishgar, F, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roba, KT, Roshandel, G, Safdarian, M, Safi, S, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Milicevic, MMS, Sartorius, B, Sepanlou, SG, Shaikh, MA, Santos Silva, DA, Singh, JA, Sobaih, BHA, Stroumpoulis, K, Abdulkader, RS, Szoeke, CEI, Temsah, M-H, Tran, BX, Ukwaja, KN, Uthman, OA, Vasankari, T, Vlassov, VV, Vollset, SE, Wakayo, T, Weintraub, RG, Wessly, PR, Wijeratne, T, Wolfe, CDA, Workicho, A, Yaghoubi, M, Yano, Y, Yaseri, M, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Jumaan, AO, Vos, T, Roth, GA, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Tehrani-Banihashemi, A, Moradi-Lakeh, M, El Bcheraoui, C, Charara, R, Khalil, I, Afshin, A, Collison, M, Daoud, F, Krohn, KJ, Chew, A, Cornaby, L, Foreman, KJ, Frostad, J, Kassebaum, NJ, Kemmer, L, Kutz, M, Liu, P, Mirarefin, M, Nguyen, G, Wang, H, Zipkin, B, Abajobir, AA, Abouzeid, M, Abu-Rmeileh, NME, Kiadaliri, AA, Ahmed, MB, Aksut, B, Alam, K, Alasfoor, D, Ali, R, Alizadeh-Navaei, R, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Arnlov, J, Asgedom, SW, Atey, TM, Awasthi, A, Baernighausen, T, Bacha, U, Barac, A, Barker-Collo, SL, Bedi, N, Bennett, DA, Berhe, DF, Biadgilign, S, Butt, ZA, Carapetis, JR, Estanislao Castro, R, Chitheer, AA, Davletov, K, Dharmaratne, SD, Djalalinia, S, Huyen, PD, Dubey, M, Ebrahimi, H, Eshrati, B, Esteghamati, A, Farvid, MS, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, SW, Gebrehiwot, TT, Gillum, RF, Gona, PN, Gupta, R, Hafezi-Nejad, N, Hamadeh, RR, Hamidi, S, Hsairi, M, Jee, SH, Jonas, JB, Karimkhani, C, Kasaeian, A, Khader, YS, Khan, EA, Kim, D, Lal, DK, Larson, HJ, Latif, AA, Linn, S, Lotufo, PA, Lunevicius, R, Abd El Razek, HM, Majeed, A, Malekzadeh, R, Malta, DC, Meier, T, Memiah, P, Memish, ZA, Mendoza, W, Mensah, GA, Meretoja, A, Miller, TR, Mirrakhimov, EM, Mohammed, S, Quyen, LN, Vuong, MN, Pearson-Stuttard, J, Pishgar, F, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Rana, SM, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roba, KT, Roshandel, G, Safdarian, M, Safi, S, Safiri, S, Sahraian, MA, Salamati, P, Samy, AM, Milicevic, MMS, Sartorius, B, Sepanlou, SG, Shaikh, MA, Santos Silva, DA, Singh, JA, Sobaih, BHA, Stroumpoulis, K, Abdulkader, RS, Szoeke, CEI, Temsah, M-H, Tran, BX, Ukwaja, KN, Uthman, OA, Vasankari, T, Vlassov, VV, Vollset, SE, Wakayo, T, Weintraub, RG, Wessly, PR, Wijeratne, T, Wolfe, CDA, Workicho, A, Yaghoubi, M, Yano, Y, Yaseri, M, Yonemoto, N, Younis, MZ, Yu, C, Zaki, MES, Jumaan, AO, Vos, T, Roth, GA, Hay, SI, Naghavi, M, and Murray, CJL

Abstract

OBJECTIVES: To report the burden of cardiovascular diseases (CVD) in the Eastern Mediterranean Region (EMR) during 1990-2015. METHODS: We used the 2015 Global Burden of Disease study for estimates of mortality and disability-adjusted life years (DALYs) of different CVD in 22 countries of EMR. RESULTS: A total of 1.4 million CVD deaths (95% UI: 1.3-1.5) occurred in 2015 in the EMR, with the highest number of deaths in Pakistan (465,116) and the lowest number of deaths in Qatar (723). The age-standardized DALY rate per 100,000 decreased from 10,080 in 1990 to 8606 in 2015 (14.6% decrease). Afghanistan had the highest age-standardized DALY rate of CVD in both 1990 and 2015. Kuwait and Qatar had the lowest age-standardized DALY rates of CVD in 1990 and 2015, respectively. High blood pressure, high total cholesterol, and high body mass index were the leading risk factors for CVD. CONCLUSIONS: The age-standardized DALY rates in the EMR are considerably higher than the global average. These findings call for a comprehensive approach to prevent and control the burden of CVD in the region.

Published
2018

13. Burden of diarrhea in the Eastern Mediterranean Region, 1990-2015: Findings from the Global Burden of Disease 2015 study

Author

Mokdad, AH, Khalil, I, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Kassebaum, NJ, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Colombara, D, Foreman, KJ, Godwin, WW, Kutz, M, Mirarefin, M, Rao, PC, Reiner, R, Troeger, C, Wang, H, Abraha, HN, Abu-Elyazeed, R, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Ahmed, MB, Alam, K, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Atey, TM, Avokpaho, EFGA, Bacha, U, Bazargan-Hejazi, S, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Bessong, PO, Beyene, AS, Bhutta, ZA, Buckle, GC, Butt, ZA, Danawi, H, Deribew, A, Djalalinia, S, Dubey, M, Endries, AY, Eshrati, B, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gugnani, HC, Hamadeh, RR, Hamidi, S, Husseini, A, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Khubchandani, J, Kissoon, N, Kopec, JA, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Memiah, P, Memish, ZA, Mendoza, W, Mengistu, DT, Mohammed, S, Murthy, S, Ngunjiri, JW, Ogbo, FA, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Ram, U, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roshandel, G, Safdarian, M, Sahraian, MA, Salamati, P, Samy, AM, Sanabria, JR, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shigematsu, M, Sobaih, BHA, Sreeramareddy, CT, Sykes, BL, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Tiruye, TY, Topor-Madry, R, Ukwaja, KN, Vollset, SE, Wakayo, T, Werdecker, A, Wiysonge, CS, Workicho, A, Yaghoubi, M, Yaseri, M, Yenesew, M, Yonemoto, N, Younis, MZ, Zaki, MES, Zodpey, S, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, Murray, CJL, Mokdad, AH, Khalil, I, El Bcheraoui, C, Charara, R, Moradi-Lakeh, M, Afshin, A, Kassebaum, NJ, Collison, M, Chew, A, Krohn, KJ, Daoud, F, Colombara, D, Foreman, KJ, Godwin, WW, Kutz, M, Mirarefin, M, Rao, PC, Reiner, R, Troeger, C, Wang, H, Abraha, HN, Abu-Elyazeed, R, Abu-Raddad, LJ, Kiadaliri, AA, Ahmadi, A, Ahmed, MB, Alam, K, Alizadeh-Navaei, R, Al-Raddadi, R, Altirkawi, KA, Alvis-Guzman, N, Anber, N, Anwari, P, Atey, TM, Avokpaho, EFGA, Bacha, U, Bazargan-Hejazi, S, Geffen, D, Bedi, N, Bensenor, IM, Berhane, A, Bessong, PO, Beyene, AS, Bhutta, ZA, Buckle, GC, Butt, ZA, Danawi, H, Deribew, A, Djalalinia, S, Dubey, M, Endries, AY, Eshrati, B, Fereshtehnejad, S-M, Fischer, F, Gebrehiwot, TT, Gugnani, HC, Hamadeh, RR, Hamidi, S, Husseini, A, James, SL, Jonas, JB, Kasaeian, A, Khader, YS, Khan, EA, Khan, G, Khubchandani, J, Kissoon, N, Kopec, JA, Koyanagi, A, Defo, BK, Larson, HJ, Latif, AA, Lunevicius, R, Abd El Razek, HM, Abd El Razek, MM, Majdzadeh, R, Majeed, A, Malekzadeh, R, Memiah, P, Memish, ZA, Mendoza, W, Mengistu, DT, Mohammed, S, Murthy, S, Ngunjiri, JW, Ogbo, FA, Pourmalek, F, Qorbani, M, Radfar, A, Rafay, A, Rahimi-Movaghar, V, Rai, RK, Ram, U, Rawaf, DL, Rawaf, S, Renzaho, AMN, Rezaei, S, Roshandel, G, Safdarian, M, Sahraian, MA, Salamati, P, Samy, AM, Sanabria, JR, Sartorius, B, Sepanlou, SG, Shaikh, MA, Shigematsu, M, Sobaih, BHA, Sreeramareddy, CT, Sykes, BL, Tehrani-Banihashemi, A, Temsah, M-H, Terkawi, AS, Tiruye, TY, Topor-Madry, R, Ukwaja, KN, Vollset, SE, Wakayo, T, Werdecker, A, Wiysonge, CS, Workicho, A, Yaghoubi, M, Yaseri, M, Yenesew, M, Yonemoto, N, Younis, MZ, Zaki, MES, Zodpey, S, Zein, B, Jumaan, AO, Vos, T, Hay, SI, Naghavi, M, and Murray, CJL

Abstract

OBJECTIVES: Diarrheal diseases (DD) are an important cause of disease burden, especially in children in low-income settings. DD can also impact children's potential livelihood through growth faltering, cognitive impairment, and other sequelae. METHODS: As part of the Global Burden of Disease study, we estimated DD burden, and the burden attributable to specific risk factors and etiologies, in the Eastern Mediterranean Region (EMR) between 1990 and 2015. We calculated disability-adjusted life-years (DALYs)-the sum of years of life lost and years lived with disability-for both sexes and all ages. RESULTS: We estimate that over 103,692 diarrhea deaths occurred in the EMR in 2015 (95% uncertainty interval: 87,018-124,692), and the mortality rate was 16.0 deaths per 100,000 persons (95% UI: 13.4-19.2). The majority of these deaths occurred in children under 5 (63.3%) (65,670 deaths, 95% UI: 53,640-79,486). DALYs per 100,000 ranged from 304 (95% UI 228-400) in Kuwait to 38,900 (95% UI 25,900-54,300) in Somalia. CONCLUSIONS: Our findings will guide evidence-based health policy decisions for interventions to achieve the ultimate goal of reducing the DD burden.

Published
2018

14. Healthcare Access and Quality Index based on mortality from causes amenable to personal health care in 195 countries and territories, 1990–2015: a novel analysis from the Global Burden of Disease Study 2015

Author

Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, Murray, CJL, Barber, RM, Fullman, N, Sorensen, RJD, Bollyky, T, McKee, M, Nolte, E, Abajobir, AA, Abate, KH, Abbafati, C, Abbas, KM, Abd-Allah, F, Abdulle, AM, Abdurahman, AA, Abera, SF, Abraham, B, Abreha, GF, Adane, K, Adelekan, AL, Adetifa, IMO, Afshin, A, Agarwal, A, Agarwal, SK, Agarwal, S, Agrawal, A, Kiadaliri, AA, Ahmadi, A, Ahmed, KY, Ahmed, MB, Akinyemi, RO, Akinyemiju, TF, Akseer, N, Al-Aly, Z, Alam, K, Alam, N, Alam, SS, Alemu, ZA, Alene, KA, Alexander, L, Ali, R, Ali, SD, Alizadeh-Navaei, R, Alkerwi, A, Alla, F, Allebeck, P, Allen, C, Al-Raddadi, R, Alsharif, U, Altirkawi, KA, Martin, EA, Alvis-Guzman, N, Amare, AT, Amini, E, Ammar, W, Amo-Adjei, J, Amoako, YA, Anderson, BO, Androudi, S, Ansari, H, Ansha, MG, Antonio, CAT, Ärnlöv, J, Artaman, A, Asayesh, H, Assadi, R, Astatkie, A, Atey, TM, Atique, S, Atnafu, NT, Atre, SR, Avila-Burgos, L, Avokpaho, EFGA, Quintanilla, BPA, Awasthi, A, Ayele, NN, Azzopardi, P, Saleem, HOB, Bärnighausen, T, Bacha, U, Badawi, A, Banerjee, A, Barac, A, Barboza, MA, Barker-Collo, SL, Barrero, LH, Basu, S, Baune, BT, Baye, K, Bayou, YT, Bazargan-Hejazi, S, Bedi, N, Beghi, E, Béjot, Y, Bello, AK, Bennett, DA, Bensenor, IM, Berhane, A, Bernabé, E, Bernal, OA, Beyene, AS, Beyene, TJ, Bhutta, ZA, Biadgilign, S, Bikbov, B, Birlik, SM, Birungi, C, Biryukov, S, Bisanzio, D, Bizuayehu, HM, Bose, D, Brainin, M, Brauer, M, Brazinova, A, Breitborde, NJK, Brenner, H, Butt, ZA, Cárdenas, R, Cahuana-Hurtado, L, Campos-Nonato, IR, Car, J, Carrero, JJ, Casey, D, Caso, V, Castañeda-Orjuela, CA, Rivas, JC, Catalá-López, F, Cecilio, P, Cercy, K, Charlson, FJ, Chen, AZ, Chew, A, Chibalabala, M, Chibueze, CE, Chisumpa, VH, Chitheer, AA, Chowdhury, R, Christensen, H, Christopher, DJ, Ciobanu, LG, Cirillo, M, Coggeshall, MS, Cooper, LT, Cortinovis, M, Crump, JA, Dalal, K, Danawi, H, Dandona, L, Dandona, R, Dargan, PI, das Neves, J, Davey, G, Davitoiu, DV, Davletov, K, De Leo, D, Del Gobbo, LC, del Pozo-Cruz, B, Dellavalle, RP, Deribe, K, Deribew, A, Des Jarlais, DC, Dey, S, Dharmaratne, SD, Dicker, D, Ding, EL, Dokova, K, Dorsey, ER, Doyle, KE, Dubey, M, Ehrenkranz, R, Ellingsen, CL, Elyazar, I, Enayati, A, Ermakov, SP, Eshrati, B, Esteghamati, A, Estep, K, Fürst, T, Faghmous, IDA, Fanuel, FBB, Faraon, EJA, Farid, TA, Farinha, CSES, Faro, A, Farvid, MS, Farzadfar, F, Feigin, VL, Feigl, AB, Fereshtehnejad, S-M, Fernandes, JG, Fernandes, JC, Feyissa, TR, Fischer, F, Fitzmaurice, C, Fleming, TD, Foigt, N, Foreman, KJ, Forouzanfar, MH, Franklin, RC, Frostad, J, G/hiwot, TT, Gakidou, E, Gambashidze, K, Gamkrelidze, A, Gao, W, Garcia-Basteiro, AL, Gebre, T, Gebremedhin, AT, Gebremichael, MW, Gebru, AA, Gelaye, AA, Geleijnse, JM, Genova-Maleras, R, Gibney, KB, Giref, AZ, Gishu, MD, Giussani, G, Godwin, WW, Gold, A, Goldberg, EM, Gona, PN, Goodridge, A, Gopalani, SV, Goto, A, Graetz, N, Greaves, F, Griswold, M, Guban, PI, Gugnani, HC, Gupta, PC, Gupta, R, Gupta, T, Gupta, V, Habtewold, TD, Hafezi-Nejad, N, Haile, D, Hailu, AD, Hailu, GB, Hakuzimana, A, Hamadeh, RR, Hambisa, MT, Hamidi, S, Hammami, M, Hankey, GJ, Hao, Y, Harb, HL, Hareri, HA, Haro, JM, Hassanvand, MS, Havmoeller, R, Hay, RJ, Hay, SI, Hendrie, D, Heredia-Pi, IB, Hoek, HW, Horino, M, Horita, N, Hosgood, HD, Htet, AS, Hu, G, Huang, H, Huang, JJ, Huntley, BM, Huynh, C, Iburg, KM, Ileanu, BV, Innos, K, Irenso, AA, Jahanmehr, N, Jakovljevic, MB, James, P, James, SL, Javanbakht, M, Jayaraman, SP, Jayatilleke, AU, Jeemon, P, Jha, V, John, D, Johnson, C, Johnson, SC, Jonas, JB, Juel, K, Kabir, Z, Kalkonde, Y, Kamal, R, Kan, H, Karch, A, Karema, CK, Karimi, SM, Kasaeian, A, Kassebaum, NJ, Kastor, A, Katikireddi, SV, Kazanjan, K, Keiyoro, PN, Kemmer, L, Kemp, AH, Kengne, AP, Kerbo, AA, Kereselidze, M, Kesavachandran, CN, Khader, YS, Khalil, I, Khan, AR, Khan, EA, Khan, G, Khang, Y-H, Khoja, ATA, Khonelidze, I, Khubchandani, J, Kibret, GD, Kim, D, Kim, P, Kim, YJ, Kimokoti, RW, Kinfu, Y, Kissoon, N, Kivipelto, M, Kokubo, Y, Kolk, A, Kolte, D, Kopec, JA, Kosen, S, Koul, PA, Koyanagi, A, Kravchenko, M, Krishnaswami, S, Krohn, KJ, Defo, BK, Bicer, BK, Kuipers, EJ, Kulkarni, VS, Kumar, GA, Kumsa, FA, Kutz, M, Kyu, HH, Lager, ACJ, Lal, A, Lal, DK, Lalloo, R, Lallukka, T, Lan, Q, Langan, SM, Lansingh, VC, Larson, HJ, Larsson, A, Laryea, DO, Latif, AA, Lawrynowicz, AEB, Leasher, JL, Leigh, J, Leinsalu, M, Leshargie, CT, Leung, J, Leung, R, Levi, M, Liang, X, Lim, SS, Lind, M, Linn, S, Lipshultz, SE, Liu, P, Liu, Y, Lo, L-T, Logroscino, G, Lopez, AD, Lorch, SA, Lotufo, PA, Lozano, R, Lunevicius, R, Lyons, RA, Macarayan, ERK, Mackay, MT, El Razek, HMA, El Razek, MMA, Mahdavi, M, Majeed, A, Malekzadeh, R, Malta, DC, Mantovani, LG, Manyazewal, T, Mapoma, CC, Marcenes, W, Marks, GB, Marquez, N, Martinez-Raga, J, Marzan, MB, Massano, J, Mathur, MR, Maulik, PK, Mazidi, M, McAlinden, C, McGrath, JJ, McNellan, C, Meaney, PA, Mehari, A, Mehndiratta, MM, Meier, T, Mekonnen, AB, Meles, KG, Memish, ZA, Mengesha, MM, Mengiste, DT, Mengistie, MA, Menota, BG, Mensah, GA, Mereta, ST, Meretoja, A, Meretoja, TJ, Mezgebe, HB, Micha, R, Millear, A, Mills, EJ, Minnig, S, Mirarefin, M, Mirrakhimov, EM, Mock, CN, Mohammad, KA, Mohammed, S, Mohanty, SK, Mokdad, AH, Mola, GLD, Molokhia, M, Monasta, L, Montico, M, Moradi-Lakeh, M, Moraga, P, Morawska, L, Mori, R, Moses, M, Mueller, UO, Murthy, S, Musa, KI, Nachega, JB, Nagata, C, Nagel, G, Naghavi, M, Naheed, A, Naldi, L, Nangia, V, Nascimento, BR, Negoi, I, Neupane, SP, Newton, CR, Ng, M, Ngalesoni, FN, Ngunjiri, JW, Nguyen, G, Ningrum, DNA, Nolte, S, Nomura, M, Norheim, OF, Norrving, B, Noubiap, JJN, Obermeyer, CM, Ogbo, FA, Oh, I-H, Okoro, A, Oladimeji, O, Olagunju, AT, Olivares, PR, Olsen, HE, Olusanya, BO, Olusanya, JO, Opio, JN, Oren, E, Ortiz, A, Osborne, RH, Osman, M, Owolabi, MO, PA, M, Pain, AW, Pakhale, S, Castillo, EP, Pana, A, Papachristou, C, Parsaeian, M, Patel, T, Patton, GC, Paudel, D, Paul, VK, Pearce, N, Pereira, DM, Perez-Padilla, R, Perez-Ruiz, F, Perico, N, Pesudovs, K, Petzold, M, Phillips, MR, Pigott, DM, Pillay, JD, Pinho, C, Polinder, S, Pond, CD, Prakash, V, Purwar, M, Qorbani, M, Quistberg, DA, Radfar, A, Rafay, A, Rahimi, K, Rahimi-Movaghar, V, Rahman, M, Rahman, MHU, Rai, RK, Ram, U, Rana, SM, Rankin, Z, Rao, PV, Rao, PC, Rawaf, S, Rego, MAS, Reitsma, M, Remuzzi, G, Renzaho, AMNN, Resnikoff, S, Rezaei, S, Rezai, MS, Ribeiro, AL, Roba, HS, Rokni, MB, Ronfani, L, Roshandel, G, Roth, GA, Rothenbacher, D, Roy, NK, Sachdev, PS, Sackey, BB, Saeedi, MY, Safiri, S, Sagar, R, Sahraian, MA, Saleh, MM, Salomon, JA, Samy, AM, Sanabria, JR, Sanchez-Niño, MD, Sandar, L, Santos, IS, Santos, JV, Milicevic, MMS, Sarmiento-Suarez, R, Sartorius, B, Satpathy, M, Savic, M, Sawhney, M, Saylan, MI, Schöttker, B, Schutte, AE, Schwebel, DC, Seedat, S, Seid, AM, Seifu, CN, Sepanlou, SG, Serdar, B, Servan-Mori, EE, Setegn, T, Shackelford, KA, Shaheen, A, Shahraz, S, Shaikh, MA, Shakh-Nazarova, M, Shamsipour, M, Islam, SMS, Sharma, J, Sharma, R, She, J, Sheikhbahaei, S, Shen, J, Shi, P, Shigematsu, M, Shin, M-J, Shiri, R, Shoman, H, Shrime, MG, Sibamo, ELS, Sigfusdottir, ID, Silva, DAS, Silveira, DGA, Sindi, S, Singh, A, Singh, JA, Singh, OP, Singh, PK, Singh, V, Sinke, AH, Sinshaw, AE, Skirbekk, V, Sliwa, K, Smith, A, Sobngwi, E, Soneji, S, Soriano, JB, Sousa, TCM, Sposato, LA, Sreeramareddy, CT, Stathopoulou, V, Steel, N, Steiner, C, Steinke, S, Stokes, MA, Stranges, S, Strong, M, Stroumpoulis, K, Sturua, L, Sufiyan, MB, Suliankatchi, RA, Sun, J, Sur, P, Swaminathan, S, Sykes, BL, Tabarés-Seisdedos, R, Tabb, KM, Taffere, GR, Talongwa, RT, Tarajia, M, Tavakkoli, M, Taveira, N, Teeple, S, Tegegne, TK, Tehrani-Banihashemi, A, Tekelab, T, Tekle, DY, Shifa, GT, Terkawi, AS, Tesema, AG, Thakur, JS, Thomson, AJ, Tillmann, T, Tiruye, TY, Tobe-Gai, R, Tonelli, M, Topor-Madry, R, Tortajada, M, Troeger, C, Truelsen, T, Tura, AK, Uchendu, US, Ukwaja, KN, Undurraga, EA, Uneke, CJ, Uthman, OA, van Boven, JFM, Van Dingenen, R, Varughese, S, Vasankari, T, Venketasubramanian, N, Violante, FS, Vladimirov, SK, Vlassov, VV, Vollset, SE, Vos, T, Wagner, JA, Wakayo, T, Waller, SG, Walson, JL, Wang, H, Wang, Y-P, Watkins, DA, Weiderpass, E, Weintraub, RG, Wen, C-P, Werdecker, A, Wesana, J, Westerman, R, Whiteford, HA, Wilkinson, JD, Wiysonge, CS, Woldeyes, BG, Wolfe, CDA, Won, S, Workicho, A, Workie, SB, Wubshet, M, Xavier, D, Xu, G, Yadav, AK, Yaghoubi, M, Yakob, B, Yan, LL, Yano, Y, Yaseri, M, Yimam, HH, Yip, P, Yonemoto, N, Yoon, S-J, Younis, MZ, Yu, C, Zaidi, Z, El Sayed Zaki, M, Zambrana-Torrelio, C, Zapata, T, Zenebe, ZM, Zodpey, S, Zoeckler, L, Zuhlke, LJ, and Murray, CJL

Published
2017

15. Evaluating e-Government services from a citizens' prespective: A reference process model

Author

Tsohou, A, Lee, H, Irani, Z, Weerakkody, V, Osman, I, Latif, AA, and Medeni, T

Subjects
ComputerSystemsOrganization_MISCELLANEOUS, Public administration, ComputingMilieux_LEGALASPECTSOFCOMPUTING, Evaluation, E-services, Reference process model
Abstract

Evaluating and optimizing e-government services is imperative for governments especially due to the capacity of e-services to transform public administrations and assist the interactions of governments with citizens, businesses and other government agencies. Existing widely applied evaluation approaches neglect to incorporate citizens’ satisfaction measures. Several citizen satisfaction models and indicators have been suggested in academia; however a reference process model that can assist practitioners to apply these performance measures is missing. In this paper we draw upon the evaluation approach proposed by the EU funded project CEES and propose a reference process model that captures re-usable practices for e-government evaluation from a citizens’ perspective. The novelty of the proposed approach is that using DEA for evaluating the e-services the assessment results in suggestions for strategic improvement of the e-services. EU FP7 Marie Curie People Project “CEES - Citizen oriented Evaluation of E-Government Systems” (reference IAPP-2008-230658)

Published
2012

17. A study of food habits of mothers and children attending rural and urban health centres in Minya, Egypt

Author

Latif Aa, Shawqi Am, Ruck Nf, and el Sharif As

Subjects
Adult, Nutrition Education, Population, Breastfeeding, Developing country, Rural Health, Nursing, Environmental health, Medicine, Humans, education, Child, Infant Nutritional Physiological Phenomena, Functional illiteracy, education.field_of_study, business.industry, Rural health, Urban Health, Infant, Feeding Behavior, Nutrition Surveys, Diet, Infectious Diseases, Family planning, Pediatrics, Perinatology and Child Health, Health education, Egypt, Female, business, Child Nutritional Physiological Phenomena, Attitude to Health
Abstract

The aims of this study were to collect information to help improve nutrition education in Minya and to train staff in research methods. A selected sample of 400 mothers each with a child aged 6 months to 2 years was taken from attenders of urban and rural health centers throughout Minya Governorate in Upper Egypt. The questionnaire used included questions on occupation and education of the mothers and their husbands family size child deaths use of the health services family planning and infant feeding. The diet of the mother and 1 child aged between 6 months and 2 years was assessed using the 24 hr recall method. All the mothers were interviewed in their homes. The interviews were followed by participant observation for 6 months of a subsample of 20 mothers. The field workers were nurses. Results show that illiteracy deliveries and child deaths per family were higher in rural than urban areas. The diets of urban and rural mothers were similar the main items being whole wheat broad broad beans ("ful medamis") and strong sweet tea. 90% of the children were currently breastfed and about 80% received supplementary food. Only rice and hot drinks were specially prepared for weaning. There were bigger differences between rural and urban areas in infant feeding practices than in the mothers diets. Urban women weaned earlier and used different types of supplementary foods. Where nutrition advice was needed it was to reinforce the already prevalent pattern of starting supplementation at 6 months and continuing breastfeeding for a year and to give information on appropriate quantities of food. The traditional practice of giving infants hot drinks should be encouraged by health educators as it decreases the incidence of dehydration caused by severe diarrhea. This is 1 of the points emerging from the survey results that could be usefully incorporated into the training of health service personnel showing the value of local research and the need for regular revision of nutrition education.

Published
1985

18. Exploring In Vitro Antibiofilm Potential and In Vivo Toxicity Assessment of Gold Nanoparticles.

Author

Liaqat I, Andleeb S, Naseem S, Ali A, Latif AA, Aftab MN, Ali S, Bibi A, Mubin M, Khalid A, Afzaal M, Yang GJ, Tufail S, and Ahmad H

Abstract

In this study, biogenically synthesized AuNPs were first characterized via UV visible spectroscopy, SEM, XRD, and FTIR followed by toxicity evaluation using mice model. UV-visible spectroscopy of biogenic AuNPs showed peaks at 540-549 nm, while FTIR spectrum showed various functional groups involving O-H, Amide I, Amide II, O-H, C-H groups, and so on. SEM showed the size variation from 30 to 60 nm. Antibacterial potential against pathogenic isolates showed bigger ZOI (31.0 mm) against Pseudomonas aeruginosa AuNPs. Antibiofilm activity showing up to 100% inhibition at 90 µg mL -1 concentration of AuNPs. Toxicity evaluation showed LD 50 as 70 mg kg -1 . Exposure to AuNPs caused significant changes in the levels of serum AST (p < 0.05) at 100-150 mg kg -1 of AuNPs exposure. Histopathology of male albino mice kidney and liver revealed that mice exposed to maximum concentration of AuNPs showed necrosis, cell distortion, and hepatocytes detachment. Present study showed that biologically synthesized AuNPs possess effective antimicrobial and biofilm inhibitory potential. AuNPs strong bactericidal effect even at lower concentration suggest that NPs could have excellent potential for combating pathogens. In conclusion, nanotechnology may revolutionize human life and medical industry by developing innovative drugs with the potential to treat diseases in shorter and noninvasive time period. Hence, in vitro biosafety and experimental observations followed by in vivo outcomes are crucial in shifting the novel therapeutics into medical practice thus leading further into their future development., (© 2024 Wiley‐VCH GmbH.)

Published
2024
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19. Interferon-induced protein 44 ( IFI44 ) and interferon regulatory factor 4 ( IRF4 ) gene expression in rheumatoid arthritis.

Author

Elsayed Ramadan Genena S, Hamouda MAF, Salama NM, Zahran ES, Abdel Latif AA, and Dawood AA

Subjects
Humans, Male, Female, Middle Aged, Case-Control Studies, Adult, Intracellular Signaling Peptides and Proteins genetics, Antigens, Cytoskeletal Proteins, Interferon Regulatory Factors genetics, Arthritis, Rheumatoid genetics, Arthritis, Rheumatoid diagnosis
Abstract

Background and Objectives: The type I interferon (IFN) signature has been found to be overactivated in many systemic autoimmune diseases. This may be explained by impaired regulation of interferon-stimulated genes (ISGs) as well as interferon-induced protein 44 (IFI44) expression via their regulatory mechanisms via interferon regulatory factors (IRFs)., Patients and Methods: This case-control study includes two groups: 50 RA patients and 50 healthy controls. The quantification of IFI44 and IRF4 expression levels by the real-time PCR technique was estimated. Disease Activity Score-28 (DAS-28) was estimated for RA patients only., Results: Among the RA patients, there were statistically significant increased ESR, CRP, TLC, RF, and anti-CCP levels ( p value < 0.001) and significant increased expression of the IFI44 and IRF4 genes ( p value < 0.001). There was a significant positive correlation between the IFI44 and IRF4, and there was a significant correlation between both and ESR and anti-CCP among RA patients. At a cutoff point of 1.95, IFI44 shows higher sensitivity and specificity values than IRF4 for the diagnosis of RA., Conclusion: IFI44 was more sensitive for RA diagnosis than IRF4. IFI44 and IRF4 overexpression could be promising predictors of RA diagnosis and might become useful clinical tools to guide therapeutic strategies.

Published
2024
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20. HAPI: An efficient Hybrid Feature Engineering-based Approach for Propaganda Identification in social media.

Author

Khanday AMUD, Wani MA, Rabani ST, Khan QR, and Abd El-Latif AA

Subjects
Humans, Support Vector Machine, Bayes Theorem, Social Media, Algorithms, Machine Learning
Abstract

Social media platforms serve as communication tools where users freely share information regardless of its accuracy. Propaganda on these platforms refers to the dissemination of biased or deceptive information aimed at influencing public opinion, encompassing various forms such as political campaigns, fake news, and conspiracy theories. This study introduces a Hybrid Feature Engineering Approach for Propaganda Identification (HAPI), designed to detect propaganda in text-based content like news articles and social media posts. HAPI combines conventional feature engineering methods with machine learning techniques to achieve high accuracy in propaganda detection. This study is conducted on data collected from Twitter via its API, and an annotation scheme is proposed to categorize tweets into binary classes (propaganda and non-propaganda). Hybrid feature engineering entails the amalgamation of various features, including Term Frequency-Inverse Document Frequency (TF-IDF), Bag of Words (BoW), Sentimental features, and tweet length, among others. Multiple Machine Learning classifiers undergo training and evaluation utilizing the proposed methodology, leveraging a selection of 40 pertinent features identified through the hybrid feature selection technique. All the selected algorithms including Multinomial Naive Bayes (MNB), Support Vector Machine (SVM), Decision Tree (DT), and Logistic Regression (LR) achieved promising results. The SVM-based HaPi (SVM-HaPi) exhibits superior performance among traditional algorithms, achieving precision, recall, F-Measure, and overall accuracy of 0.69, 0.69, 0.69, and 69.2%, respectively. Furthermore, the proposed approach is compared to well-known existing approaches where it overperformed most of the studies on several evaluation metrics. This research contributes to the development of a comprehensive system tailored for propaganda identification in textual content. Nonetheless, the purview of propaganda detection transcends textual data alone. Deep learning algorithms like Artificial Neural Networks (ANN) offer the capability to manage multimodal data, incorporating text, images, audio, and video, thereby considering not only the content itself but also its presentation and contextual nuances during dissemination., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Khanday et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Published
2024
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21. Cyclic quantum teleportation of two-qubit entangled states by using six-qubit cluster state and six-qubit entangled state.

Author

Slaoui A, El Kirdi M, Ahl Laamara R, Alabdulhafith M, Chelloug SA, and Abd El-Latif AA

Abstract

Cyclic quantum teleportation schemes requires at least the existence of three collaborators acting all as senders and receivers of quantum information, each one of them has an information to be transmitted to the next neighbour in a circular manner. Here, new cyclic quantum teleportation scheme is proposed for perfectly transmitting cyclically three arbitrary unknown two-qubit states ( α , β and γ ) among the three collaborators. In this scheme, Alice can send to Bob the quantum information contained in her two-qubit state α and receive from Charlie the quantum information contained in the two-qubit state in his possession γ and similarly, Bob can transmit to Charlie the quantum information contained in his two-qubit state β through a quantum channel of twelve-qubit state consisting of a six-qubit cluster state and a six-qubit entangled state by sequentially and cyclically performing Bell state measurements. Subsequently, each one of the three participants can afterwards retrieve his own desired two-qubit state using classical channel and by performing appropriate unitary Pauli operators and we have shown that our proposed scheme performs efficiently., (© 2024. The Author(s).)

Published
2024
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22. The effect of use of alpha-blockers in posterior urethral valve pediatric patients postvalve ablation in the absence of further outlet obstruction.

Author

Aboulela WN, Eladawy MS, and Latif AA

Abstract

Objectives: The objectives of this study were to detect whether the use of alpha-blockers in posterior urethral valve (PUV) pediatric patients after valve ablation will improve the persistent obstructive symptoms despite the absence of obstruction and if there are associated side effects of its use., Patients and: Methods: A prospective, single-blinded randomized study was conducted at the urology department of two hospitals on 50 male children between September 2019 and June 2021 with PUV. All children were treated by endoscopic ablation of PUV using the cold knife and were followed clinically for voiding symptoms and with ultrasonography and laboratory tests. All patients underwent second-look cystoscopy 1 month after primary valve ablation to see residual valves as a routine procedure confirming no remnant of the valve and still complaining of obstructive symptoms. They were divided into two equal groups 25 patients each. Group A was given alpha-blockers and Group B placebo for 1 month., Results: Marked improvement of obstructive symptoms in Group A reaching about 90% (21 patients), whereas no mentioned improvement in Group B was noticed with no side effects of both medication the alpha-blocker and the placebo during its use., Conclusion: The use of alpha-blockers improves the obstructive symptoms in pediatric patients with PUV after valve ablation and in the absence of any further urethral obstruction with no side effects noticed during the period of its use., Competing Interests: There are no conflicts of interest., (Copyright: © 2024 Urology Annals.)

Published
2024
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23. A nucleic acid-based surface-enhanced Raman scattering of gold nanorods in N-gene integrated principal component analysis for COVID-19 detection.

Author

Mustapa MA, Yuzir A, Latif AA, Ambran S, and Abdullah N

Subjects
Humans, Spectrum Analysis, Raman methods, Gold, Principal Component Analysis, SARS-CoV-2 genetics, Nucleocapsid, Metal Nanoparticles, Nucleic Acids, COVID-19 diagnosis, Nanotubes
Abstract

A rapid, simple, sensitive, and selective point-of-care diagnosis tool kit is vital for detecting the coronavirus disease (COVID-19) based on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain. Currently, the reverse transcriptase-polymerase chain reaction (RT-PCR) is the best technique to detect the disease. Although a good sensitivity has been observed in RT-PCR, the isolation and screening process for high sample volume is limited due to the time-consuming and laborious work. This study introduced a nucleic acid-based surface-enhanced Raman scattering (SERS) sensor to detect the nucleocapsid gene (N-gene) of SARS-CoV-2. The Raman scattering signal was amplified using gold nanoparticles (AuNPs) possessing a rod-like morphology to improve the SERS effect, which was approximately 12-15 nm in diameter and 40-50 nm in length. These nanoparticles were functionalised with the single-stranded deoxyribonucleic acid (ssDNA) complemented with the N-gene. Furthermore, the study demonstrates method selectivity by strategically testing the same virus genome at different locations. This focused approach showcases the method's capability to discern specific genetic variations, ensuring accuracy in viral detection. A multivariate statistical analysis technique was then applied to analyse the raw SERS spectra data using the principal component analysis (PCA). An acceptable variance amount was demonstrated by the overall variance (82.4 %) for PC1 and PC2, which exceeded the desired value of 80 %. These results successfully revealed the hidden information in the raw SERS spectra data. The outcome suggested a more significant thymine base detection than other nitrogenous bases at wavenumbers 613, 779, 1219, 1345, and 1382 cm -1 . Adenine was also less observed at 734 cm -1 , and ssDNA-RNA hybridisations were presented in the ketone with amino base SERS bands in 1746, 1815, 1871, and 1971 cm -1 of the fingerprint. Overall, the N-gene could be detected as low as 0.1 nM within 10 mins of incubation time. This approach could be developed as an alternative point-of-care diagnosis tool kit to detect and monitor the COVID-19 disease., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Published
2024
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24. Molecular and serological prevalence of corridor disease (buffalo associated Theileria parva infection) in cattle populations at the livestock/game interface of KwaZulu-Natal province, South Africa.

Author

Mbizeni S, Mans BJ, Mukaratirwa S, Peba B, Maboko BB, Pienaar R, Magampa H, Marumo RD, Josemans A, Troskie C, and Latif AA

Subjects
Animals, Cattle, Buffaloes, Livestock, South Africa epidemiology, Cross-Sectional Studies, Prevalence, Seroepidemiologic Studies, Theileriasis epidemiology, Theileria parva, Bison, Cattle Diseases epidemiology
Abstract

Theileria parva are intracellular protozoal parasites responsible for three disease syndromes in cattle, namely East Coast fever (ECF), Corridor disease (CD) and Zimbabwean theileriosis. The increase in reports of CD outbreaks in recent years has raised questions about the probability of adaptation of buffalo-derived T. parva strains in cattle herds adjacent to game reserves. A cross-sectional study was conducted from March 2016 to December 2018 to investigate the extent of occurrence of T. parva infections in cattle in the CD-controlled area of KwaZulu-Natal Province. Blood samples were collected from 1137 cattle from 14 herds and analysed by quantitative real-time PCR (qPCR) and indirect fluorescent antibody test (IFAT) to determine the prevalence of T. parva. A total of 484 samples from 4 of the 14 herds were further tested on qPCR for the presence of T. taurotragi infections. The data were analysed using descriptive statistics and a chi-square test was used to assess association between variables. The overall prevalence of T. parva was 1.3% (95%CI:1-2%) and 19.9% (95%CI:17-22%) on qPCR and IFAT, respectively. The qPCR positive samples were detected in March and May while IFAT positive samples were detected in all seasons sampled, with higher numbers during summer months. The Pearson Chi-squared test showed that T. parva prevalence rates based on both qPCR and IFAT were positively associated with herds with previous history of CD outbreaks (χ 2  = 8.594, p = 0.003; χ 2  = 69.513, p < 0.001, respectively). The overall prevalence of T. taurotragi was 39.4% (95% CI: 35-44%) with the herd-level prevalence ranging between 35.0% and 43.4%. Possible cross-reaction of T. parva IFAT to T. taurotragi was detected on few samples, however, there was no significant association between T. taurotragi infections and IFAT positivity (χ 2  = 0.829, p = 0.363). Results from this study demonstrated the extent of occurrence of subclinical carriers and the level of exposure to T. parva infections in cattle populations at a livestock/game interface area of KwaZulu-Natal Province. The molecular and seroprevalence rates were low when compared with other areas where cattle-adapted T. parva infections are endemic. The adaptation of buffalo-derived T. parva in cattle population resulting in cattle-cattle transmissions seem to be unlikely under the current epidemiological state., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Published
2024
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25. WITHDRAWN: The Effect of Preoperative Intravenous Tranexamic Acid Versus Rectal Misoprostol in Reducing Blood Loss During and After Elective Cesarean Delivery in Primigravida: A Double-Blinded, Randomized, Comparative-Placebo Trial.

Author

Afifi AN, Taymour MA, Mahmoud SI, Zolfokar DS, Moghazy Salman MS, El-Hafeez Abd El-Latif AA, and El-Khayat WM

Abstract

The publisher regrets that this article has been temporarily removed. A replacement will appear as soon as possible in which the reason for the removal of the article will be specified, or the article will be reinstated. The full Elsevier Policy on Article Withdrawal can be found at: https://www.elsevier.com/about/policies/article-withdrawal., (Copyright © 2023 The Society of Obstetricians and Gynaecologists of Canada/La Société des obstétriciens et gynécologues du Canada. Published by Elsevier Inc. All rights reserved.)

Published
2023
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26. Mechanical and radiation shielding characterization of W-based alloys for advanced nuclear unit.

Author

Al-Shelkamy SA, Vega-Carrillo HR, Xie Z, El-Hossary FM, Mosa ES, Mahdy AA, Elkady O, Ghafaar MA, and M AA

Abstract

The paper aims to investigate the mechanical and radiation shielding properties of two tungsten-based alloys manufactured by powder technology; their features when compared with two standard stainless steel grades for advanced nuclear applications. Multiple measurements were performed to characterize the alloys' structural and mechanical properties. XRD analysis and average surface roughness measurements showed the crystalline and morphological structure of the alloys. Surface microhardness added to the abrasive wear analysis showed the final wear resistance of the selected alloys. In addition, the shielding features against gamma and fast neutrons radiation were calculated. The superior characteristics of W-based alloys manufactured by powder technology make them suitable to be used in advanced nuclear power units., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Published
2023
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27. Emotional intelligence, workplace conflict and job burn-out among critical care physicians: a mediation analysis with a cross-sectional study design in Egypt.

Author

Kasemy ZA, Sharif AF, Bahgat NM, Abdelsattar S, and Abdel Latif AA

Subjects
Humans, Cross-Sectional Studies, Egypt, Mediation Analysis, Workplace psychology, Emotional Intelligence, Job Satisfaction, Surveys and Questionnaires, Burnout, Professional psychology, Physicians
Abstract

Objectives: This study aimed to examine the association between the effect of emotional intelligence on job burn-out and the mediating effect of workplace conflict management among critical care physicians., Design and Setting: A cross-sectional study design was deployed., Participants: The studied sample comprised 144 critical care physicians working at two Egyptian tertiary care public hospitals., Measures: The participants' responses to three questionnaires were studied, including the Maslach Burnout Inventory, the Emotional Intelligence Questionnaire and the Conflict Management Formative Questionnaire, in addition to assessing coenzyme Q10 (CoQ10) levels., Results: Among the anaesthesiologists and critical care specialists examined, burn-out was reported by 63.9% of them. The findings of this study indicated that emotional intelligence played a notable role in predicting job burn-out, with a negative impact. Further analysis revealed that workplace conflict management acted as a mediator between emotional intelligence and the three components of job burn-out. Additionally, age and years of experience were found to have a negative correlation with burn-out and a positive correlation with conflict management. Furthermore, CoQ10 levels showed a negative correlation with burn-out, while displaying positive correlations with emotional intelligence and conflict management., Conclusion: Conflict management acted as a mediator in reducing burn-out by demonstrating a significant negative relationship between emotional intelligence and burn-out. Initial findings indicated that possessing good emotional intelligence and conflict management skills had a positive influence on the immune system, as evidenced by higher CoQ10 levels. However, burn-out had the opposite effect, depleting the body's CoQ10 stores and negatively impacting immune-protective mechanisms. Therefore, it is crucial to implement emotional management educational programmes and update educational policies and pedagogical practices to enhance the emotional capabilities of healthcare providers, especially in demanding fields like critical care, to effectively address conflicts., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Published
2023
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28. Synthesis of PVP-capped trimetallic nanoparticles and their efficient catalytic degradation of organic dyes.

Author

Memon K, Memon R, Khalid A, Al-Anzi BS, Uddin S, Sherazi STH, Chandio A, Talpur FN, Latif AA, and Liaqat I

Abstract

The study proposes a simple and efficient way to synthesize a heterogeneous catalyst that can be used for the degradation of organic dyes. A simple and fast chemical process was employed to synthesize Au: Ni: Co tri-metal nanohybrid structures, which were used as a catalyst to eliminate toxic organic dye contamination from wastewater in textile industries. The catalyst's performance was tested by degrading individual dyes as well as mixtures of dyes such as methylene blue (MB), methyl orange (MO), methyl red (MR), and Rose Bengal (RB) at various time intervals. The experimental results show the catalytic high degradation efficiency of different dyes achieving 72-90% rates in 29 s. Moreover, the material displayed excellent recycling stability, maintaining its degradation efficiency over four consecutive runs without any degradation in performance. Overall, the findings of the study suggest that these materials possess efficient catalytic properties, opening avenues toward their use in clean energy alternatives, environmental remediation, and other biological applications., Competing Interests: The authors have no conflict of interest to declare., (This journal is © The Royal Society of Chemistry.)

Published
2023
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29. The potential role of upregulated PARP-1/RIPK1 expressions in amikacin-induced oxidative damage and nephrotoxicity in Wistar rats.

Author

El Latif AA, Zahra AEA, Badr A, Elbialy ZI, Alghamdi AAA, Althobaiti NA, Assar DH, and Abouzed TK

Abstract

This study aimed to investigate the gene expression levels associated with nephrotoxic action of amikacin, as well as the post-treatment effect of diuretics on its nephrotoxic effects. Sixty male rats were divided equally into six groups, including the control group receiving saline intra-peritoneally (ip), and the five treated groups including therapeutic and double therapeutic dose groups, injected ip (15 and 30 mg/kg b.wt./day) respectively for seven days, and another two rat groups treated as therapeutic and double therapeutic dose groups then administered the diuretic orally for seven days and the last group received amikacin ip at a rate of 15 mg/kg/day for seven days, then given free access to water without diuretics for another seven days and was kept as a self-recovery group. Amikacin caused kidney injury, which was exacerbated by the double therapeutic dose, as evidenced by abnormal serum renal injury biomarkers, elevated renal MDA levels, inhibition of renal catalase and SOD enzyme activities, with renal degenerative and necrotic changes. Moreover, comet assays also revealed renal DNA damage. Interestingly, amikacin administration markedly elevated expression levels of the PARP-1 , RIP1 , TNF- α, IL-1β , and iNOS genes as compared to the control group. However, compared to the self-recovery group, post-amikacin diuretic treatment modulates amikacin-induced altered findings and alleviates amikacin nephrotoxic effects more efficiently. Our findings suggested the potential role of PARP-1 and RIPK1 expressions that influence the expression of proinflammatory cytokines such as IL-1β and TNF-α by exaggerating oxidative stress which may contribute to the pathogenesis of amikacin-induced nephrotoxicity., Competing Interests: The authors declare that they have no known competing financial interests., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Published
2023
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30. In Vitro Biofilm-Mediated Biodegradation of Pesticides and Dye-Contaminated Effluents Using Bacterial Biofilms.

Author

Liaqat I, Khalid A, Rubab S, Rashid F, Latif AA, Naseem S, Bibi A, Khan BN, Ansar W, Javed A, Afzaal M, Summer M, Majid S, Ali S, and Aftab MN

Abstract

Overuse of pesticides in agricultural soil and dye-polluted effluents severely contaminates the environment and is toxic to animals and humans making their removal from the environment essential. The present study aimed to assess the biodegradation of pesticides (cypermethrin (CYP) and imidacloprid (IMI)), and dyes (malachite green (MG) and Congo red (CR)) using biofilms of bacteria isolated from pesticide-contaminated soil and dye effluents. Biofilms of indigenous bacteria, i.e., Bacillus thuringiensis 2A (OP554568), Enterobacter hormaechei 4A (OP723332), Bacillus sp. 5A (OP586601), and Bacillus cereus 6B (OP586602) individually and in mixed culture were tested against CYP and IMI. Biofilms of indigenous bacteria i.e., Lysinibacillus sphaericus AF1 (OP589134), Bacillus sp. CF3 (OP589135) and Bacillus sp. DF4 (OP589136) individually and in mixed culture were tested for their ability to degrade dyes. The biofilm of a mixed culture of B. thuringiensis + Bacillus sp. (P7) showed 46.2% degradation of CYP compared to the biofilm of a mixed culture of B. thuringiensis + E. hormaechei + Bacillus sp. + B. cereus (P11), which showed significantly high degradation (70.0%) of IMI. Regarding dye biodegradation, a mixed culture biofilm of Bacillus sp. + Bacillus sp. (D6) showed 86.76% degradation of MG, which was significantly high compared to a mixed culture biofilm of L. sphaericus + Bacillus sp. (D4) that degraded only 30.78% of CR. UV-VIS spectroscopy revealed major peaks at 224 nm, 263 nm, 581 nm and 436 nm for CYP, IMI, MG and CR, respectively, which completely disappeared after treatment with bacterial biofilms. Fourier transform infrared (FTIR) analysis showed the appearance of new peaks in degraded metabolites and disappearance of a peak in the control spectrum after biofilm treatment. Thin layer chromatography (TLC) analysis also confirmed the degradation of CYP, IMI, MG and CR into several metabolites compared to the control. The present study demonstrates the biodegradation potential of biofilm-forming bacteria isolated from pesticide-polluted soil and dye effluents against pesticides and dyes. This is the first report demonstrating biofilm-mediated bio-degradation of CYP, IMI, MG and CR utilizing soil and effluent bacterial flora from Multan and Sheikhupura, Punjab, Pakistan.

Published
2023
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31. Internet of Medical Things and Healthcare 4.0: Trends, Requirements, Challenges, and Research Directions.

Author

Osama M, Ateya AA, Sayed MS, Hammad M, Pławiak P, Abd El-Latif AA, and Elsayed RA

Subjects
Humans, Artificial Intelligence, Internet, Biological Evolution, Internet of Things, Telemedicine
Abstract

Healthcare 4.0 is a recent e-health paradigm associated with the concept of Industry 4.0. It provides approaches to achieving precision medicine that delivers healthcare services based on the patient's characteristics. Moreover, Healthcare 4.0 enables telemedicine, including telesurgery, early predictions, and diagnosis of diseases. This represents an important paradigm for modern societies, especially with the current situation of pandemics. The release of the fifth-generation cellular system (5G), the current advances in wearable device manufacturing, and the recent technologies, e.g., artificial intelligence (AI), edge computing, and the Internet of Things (IoT), are the main drivers of evolutions of Healthcare 4.0 systems. To this end, this work considers introducing recent advances, trends, and requirements of the Internet of Medical Things (IoMT) and Healthcare 4.0 systems. The ultimate requirements of such networks in the era of 5G and next-generation networks are discussed. Moreover, the design challenges and current research directions of these networks. The key enabling technologies of such systems, including AI and distributed edge computing, are discussed.

Published
2023
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32. Antibacterial and Cytotoxic Effects of Biosynthesized Zinc Oxide and Titanium Dioxide Nanoparticles.

Author

Habib S, Rashid F, Tahir H, Liaqat I, Latif AA, Naseem S, Khalid A, Haider N, Hani U, Dawoud RA, Modafer Y, Bibi A, and Jefri OA

Abstract

Nanotechnology is a rapidly developing field of research that studies materials having dimensions of less than 100 nanometers. It is applicable in many areas of life sciences and medicine including skin care and personal hygiene, as these materials are the essential components of various cosmetics and sunscreens. The aim of the present study was to synthesize Zinc oxide (ZnO) and Titanium dioxide (TiO 2 ) nanoparticles (NPs) by using Calotropis procera ( C. procera ) leaf extract. Green synthesized NPs were characterized by UV spectroscopy, Fourier transform infrared (FTIR), X-ray diffraction (XRD), and Scanning Electron Microscopy (SEM) to investigate their structure, size, and physical properties. The antibacterial and synergistic effects of ZnO and TiO 2 NPs along with antibiotics were also observed against bacterial isolates. The antioxidant activity of synthesized NPs was analyzed by their α-diphenyl-β-picrylhydrazyl (DPPH) radical scavenging activity. In vivo toxic effects of the synthesized NPs were evaluated in albino mice at different doses (100, 200, and 300 mg/kg body weight) of ZnO and TiO 2 NPs administered orally for 7, 14, and 21 days. The antibacterial results showed that the zone of inhibition (ZOI) was increased in a concentration-dependent manner. Among the bacterial strains, Staphylococcus aureus showed the highest ZOI, i.e., 17 and 14 mm against ZnO and TiO 2 NPs, respectively, while Escherichia coli showed the lowest ZOI, i.e., 12 and 10 mm, respectively. Therefore, ZnO NPs are potent antibacterial agents compared to TiO 2 NPs. Both NPs showed synergistic effects with antibiotics (ciprofloxacin and imipenem). Moreover, the DPPH activity showed that ZnO and TiO 2 NPs have significantly ( p > 0.05) higher antioxidant activity, i.e., 53% and 58.7%, respectively, which indicated that TiO 2 has good antioxidant potential compared to ZnO NPs. However, the histological changes after exposure to different doses of ZnO and TiO 2 NPs showed toxicity-related changes in the structure of the kidney compared to the control group. The current study provided valuable information about the antibacterial, antioxidant, and toxicity impacts of green synthesized ZnO and TiO 2 NPs, which can be influential in the further study of their eco-toxicological effects.

Published
2023
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33. Efficient Brain Tumor Detection with Lightweight End-to-End Deep Learning Model.

Author

Hammad M, ElAffendi M, Ateya AA, and Abd El-Latif AA

Abstract

In the field of medical imaging, deep learning has made considerable strides, particularly in the diagnosis of brain tumors. The Internet of Medical Things (IoMT) has made it possible to combine these deep learning models into advanced medical devices for more accurate and efficient diagnosis. Convolutional neural networks (CNNs) are a popular deep learning technique for brain tumor detection because they can be trained on vast medical imaging datasets to recognize cancers in new images. Despite its benefits, which include greater accuracy and efficiency, deep learning has disadvantages, such as high computing costs and the possibility of skewed findings due to inadequate training data. Further study is needed to fully understand the potential and limitations of deep learning in brain tumor detection in the IoMT and to overcome the obstacles associated with real-world implementation. In this study, we propose a new CNN-based deep learning model for brain tumor detection. The suggested model is an end-to-end model, which reduces the system's complexity in comparison to earlier deep learning models. In addition, our model is lightweight, as it is built from a small number of layers compared to other previous models, which makes the model suitable for real-time applications. The optimistic findings of a rapid increase in accuracy (99.48% for binary class and 96.86% for multi-class) demonstrate that the new framework model has excelled in the competition. This study demonstrates that the suggested deep model outperforms other CNNs for detecting brain tumors. Additionally, the study provides a framework for secure data transfer of medical lab results with security recommendations to ensure security in the IoMT.

Published
2023
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34. Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations.

Author

Gangavarapu K, Latif AA, Mullen JL, Alkuzweny M, Hufbauer E, Tsueng G, Haag E, Zeller M, Aceves CM, Zaiets K, Cano M, Zhou X, Qian Z, Sattler R, Matteson NL, Levy JI, Lee RTC, Freitas L, Maurer-Stroh S, Suchard MA, Wu C, Su AI, Andersen KG, and Hughes LD

Subjects
Humans, Genomics, Disease Outbreaks, Mutation, SARS-CoV-2, COVID-19
Abstract

In response to the emergence of SARS-CoV-2 variants of concern, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info , a platform that currently tracks over 40 million combinations of Pango lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials and the general public. We describe the interpretable visualizations available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data and the server infrastructure that enables widespread data dissemination via a high-performance API that can be accessed using an R package. We show how outbreak.info can be used for genomic surveillance and as a hypothesis-generation tool to understand the ongoing pandemic at varying geographic and temporal scales., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2023
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35. Outbreak.info Research Library: a standardized, searchable platform to discover and explore COVID-19 resources.

Author

Tsueng G, Mullen JL, Alkuzweny M, Cano M, Rush B, Haag E, Lin J, Welzel DJ, Zhou X, Qian Z, Latif AA, Hufbauer E, Zeller M, Andersen KG, Wu C, Su AI, Gangavarapu K, and Hughes LD

Subjects
Humans, SARS-CoV-2, Disease Outbreaks, COVID-19
Abstract

Outbreak.info Research Library is a standardized, searchable interface of coronavirus disease 2019 (COVID-19) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) publications, clinical trials, datasets, protocols and other resources, built with a reusable framework. We developed a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public application programming interface (API) and R package., (© 2023. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Published
2023
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36. Intelligent computational methods for multi-unmanned aerial vehicle-enabled autonomous mobile edge computing systems.

Author

Asim M and Abd El-Latif AA

Abstract

This paper proposes a multi-unmanned aerial vehicle (UAV)-enabled autonomous mobile edge computing (MEC) system, in which several UAVs are deployed to provide services to user devices (UDs). The aim is to reduce/minimize the overall energy consumption of the autonomous system via designing the optimal trajectories of multiple UAVs. The problem is very complicated to be solved by traditional methods, as one has to take into account the deployment updation of stop points (SPs), the association of SPs with UDs and UAVs, and the optimal trajectories designing of UAVs. To tackle this problem, we propose a variable-length trajectory planning algorithm (VLTPA) consisting of three phases. In the first phase, the deployment of SPs is updated via presenting a genetic algorithm (GA) having variable-length individuals. Accordingly, the association between UDs and SPs is addressed by using a close rule. Finally, a multi-chrome GA is proposed to jointly handle the association of SPs with UAVs and their order for UAVs. The proposed VLTPA is tested via performing extensive experiments on eight instances ranging from 60 to 200 UDs, which reveal that the proposed VLTPA outperforms other compared state-of-the-art algorithms., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2021 ISA. Published by Elsevier Ltd. All rights reserved.)

Published
2023
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37. Electrodeposited Cobalt Nanosheets on Smooth Silver as a Bifunctional Catalyst for OER and ORR: In Situ Structural and Catalytic Characterization.

Author

Zan L, Amin HMA, Mostafa E, Abd-El-Latif AA, Iqbal S, and Baltruschat H

Abstract

Developing earth-abundant, cost-effective, and active bifunctional electrocatalysts for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) is key to boosting sustainable energy systems such as electrolyzers and lithium-air batteries. However, the performance of promising cobalt-based materials is impaired by the external effects of binders and carbon additives as well as inhomogeneous electrode fabrication. In this work, binder- and carbon-free flower-like Co-decorated Ag catalytic nanosheets were in situ-synthesized via a simple electrodeposition approach. The morphology, composition, and structure of Co/Ag before and after OER were characterized using scanning electron microscopy (SEM), energy-dispersive X-ray (EDX), X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD). Co/Ag thin film electrodes with various Co contents exhibited a bifunctional activity toward ORR and OER due to a synergistic effect. XPS analysis suggested the formation of Co 3 O 4 as the main active species for OER. In particular, Co (83%)/Ag surface revealed a 60 mV lower ORR overpotential than a pure Ag surface and even lower than drop-casted Co 3 O 4 nanoparticles on Ag surface. Only 1.5% peroxide was generated, suggesting a four-electron transfer ORR. In addition, the OER onset potential on Co/Ag is 60 mV less than Co 3 O 4 . Tafel slopes of 71 and 75 mV dec -1 were obtained for ORR and OER, respectively. Importantly, the three-dimensional (3D) growth mechanism of a cobalt layer (∼1 nm) on a well-defined atomic smooth Ag surface is unraveled by in situ electrochemical scanning tunneling microscopy (EC-STM). EC-STM suggests that Co prefers to nucleate at the step edges of Ag and grows in a 3D, forming nanoparticles, where the deposition/dissolution process of the Co adlayer on Ag is reversible. This investigation may provide insights into design strategies of efficient oxygen electrocatalysts.

Published
2022
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38. Outbreak.info Research Library: A standardized, searchable platform to discover and explore COVID-19 resources.

Author

Tsueng G, Mullen JL, Alkuzweny M, Cano M, Rush B, Haag E, Curators O, Lin J, Welzel DJ, Zhou X, Qian Z, Latif AA, Hufbauer E, Zeller M, Andersen KG, Wu C, Su AI, Gangavarapu K, and Hughes LD

Abstract

To combat the ongoing COVID-19 pandemic, scientists have been conducting research at breakneck speeds, producing over 52,000 peer-reviewed articles within the first year. To address the challenge in tracking the vast amount of new research located in separate repositories, we developed outbreak.info Research Library, a standardized, searchable interface of COVID-19 and SARS-CoV-2 resources. Unifying metadata from sixteen repositories, we assembled a collection of over 350,000 publications, clinical trials, datasets, protocols, and other resources as of October 2022. We used a rigorous schema to enforce consistency across different sources and resource types and linked related resources. Researchers can quickly search the latest research across data repositories, regardless of resource type or repository location, via a search interface, public API, and R package. Finally, we discuss the challenges inherent in combining metadata from scattered and heterogeneous resources and provide recommendations to streamline this process to aid scientific research., Competing Interests: Conflicts of Interest KGA has received consulting fees and/or compensated expert testimony on SARS-CoV-2 and the COVID-19 pandemic.

Published
2022
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39. Amplification and sequencing of entire tick mitochondrial genomes for a phylogenomic analysis.

Author

Kneubehl AR, Muñoz-Leal S, Filatov S, de Klerk DG, Pienaar R, Lohmeyer KH, Bermúdez SE, Suriyamongkol T, Mali I, Kanduma E, Latif AA, Sarih M, Bouattour A, de León AAP, Teel PD, Labruna MB, Mans BJ, and Lopez JE

Subjects
Humans, Animals, Phylogeny, Sequence Analysis, DNA, High-Throughput Nucleotide Sequencing methods, Genome, Mitochondrial genetics, Ticks genetics
Abstract

The mitochondrial genome (mitogenome) has proven to be important for the taxonomy, systematics, and population genetics of ticks. However, current methods to generate mitogenomes can be cost-prohibitive at scale. To address this issue, we developed a cost-effective approach to amplify and sequence the whole mitogenome of individual tick specimens. Using two different primer sites, this approach generated two full-length mitogenome amplicons that were sequenced using the Oxford Nanopore Technologies' Mk1B sequencer. We used this approach to generate 85 individual tick mitogenomes from samples comprised of the three tick families, 11 genera, and 57 species. Twenty-six of these species did not have a complete mitogenome available on GenBank prior to this work. We benchmarked the accuracy of this approach using a subset of samples that had been previously sequenced by low-coverage Illumina genome skimming. We found our assemblies were comparable or exceeded the Illumina method, achieving a median sequence concordance of 99.98%. We further analyzed our mitogenome dataset in a mitophylogenomic analysis in the context of all three tick families. We were able to sequence 72 samples in one run and achieved a cost/sample of ~ $10 USD. This cost-effective strategy is applicable for sample identification, taxonomy, systematics, and population genetics for not only ticks but likely other metazoans; thus, making mitogenome sequencing equitable for the wider scientific community., (© 2022. The Author(s).)

Published
2022
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40. Regional connectivity drove bidirectional transmission of SARS-CoV-2 in the Middle East during travel restrictions.

Author

Parker E, Anderson C, Zeller M, Tibi A, Havens JL, Laroche G, Benlarbi M, Ariana A, Robles-Sikisaka R, Latif AA, Watts A, Awidi A, Jaradat SA, Gangavarapu K, Ramesh K, Kurzban E, Matteson NL, Han AX, Hughes LD, McGraw M, Spencer E, Nicholson L, Khan K, Suchard MA, Wertheim JO, Wohl S, Côté M, Abdelnour A, Andersen KG, and Abu-Dayyeh I

Subjects
Humans, Middle East epidemiology, Pandemics prevention & control, Travel, COVID-19 epidemiology, SARS-CoV-2
Abstract

Regional connectivity and land travel have been identified as important drivers of SARS-CoV-2 transmission. However, the generalizability of this finding is understudied outside of well-sampled, highly connected regions. In this study, we investigated the relative contributions of regional and intercontinental connectivity to the source-sink dynamics of SARS-CoV-2 for Jordan and the Middle East. By integrating genomic, epidemiological and travel data we show that the source of introductions into Jordan was dynamic across 2020, shifting from intercontinental seeding in the early pandemic to more regional seeding for the travel restrictions period. We show that land travel, particularly freight transport, drove introduction risk during the travel restrictions period. High regional connectivity and land travel also drove Jordan's export risk. Our findings emphasize regional connectedness and land travel as drivers of transmission in the Middle East., (© 2022. The Author(s).)

Published
2022
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41. Percutaneous Intervention of Cabrol Graft-Left Main Anastomosis.

Author

Ahmed T, Alhazmi L, Latif AA, Arbune A, Sekela M, and Leventhal A

Subjects
Anastomosis, Surgical, Aorta surgery, Coronary Vessels diagnostic imaging, Coronary Vessels surgery, Humans, Blood Vessel Prosthesis, Coronary Stenosis diagnostic imaging, Coronary Stenosis surgery
Abstract

The Cabrol technique involves surgical reimplantation of coronary arteries after aortic root replacement. It uses a Dacron graft interposed between the aortic root graft and the native coronary artery. A stenosis of the graft-coronary anastomosis requires either surgical or percutaneous correction. An understanding of the Cabrol and modified Cabrol techniques and the associated anatomy is essential for a successful percutaneous intervention. We report a case of percutaneous intervention of a Cabrol graft-left main coronary artery stenosis in a patient who presented with exertional angina., Competing Interests: Authors' declarations We assure that:, (Copyright © 2022. Published by Elsevier Inc.)

Published
2022
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42. Outbreak.info genomic reports: scalable and dynamic surveillance of SARS-CoV-2 variants and mutations.

Author

Gangavarapu K, Latif AA, Mullen JL, Alkuzweny M, Hufbauer E, Tsueng G, Haag E, Zeller M, Aceves CM, Zaiets K, Cano M, Zhou J, Qian Z, Sattler R, Matteson NL, Levy JI, Lee RT, Freitas L, Maurer-Stroh S, Suchard MA, Wu C, Su AI, Andersen KG, and Hughes LD

Abstract

The emergence of SARS-CoV-2 variants of concern has prompted the need for near real-time genomic surveillance to inform public health interventions. In response to this need, the global scientific community, through unprecedented effort, has sequenced and shared over 11 million genomes through GISAID, as of May 2022. This extraordinarily high sampling rate provides a unique opportunity to track the evolution of the virus in near real-time. Here, we present outbreak.info, a platform that currently tracks over 40 million combinations of PANGO lineages and individual mutations, across over 7,000 locations, to provide insights for researchers, public health officials, and the general public. We describe the interpretable and opinionated visualizations in the variant and location focussed reports available in our web application, the pipelines that enable the scalable ingestion of heterogeneous sources of SARS-CoV-2 variant data, and the server infrastructure that enables widespread data dissemination via a high performance API that can be accessed using an R package. We present a case study that illustrates how outbreak.info can be used for genomic surveillance and as a hypothesis generation tool to understand the ongoing pandemic at varying geographic and temporal scales. With an emphasis on scalability, interactivity, interpretability, and reusability, outbreak.info provides a template to enable genomic surveillance at a global and localized scale.

Published
2022
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43. Patient-related factors associated with medication adherence behavior in patients with end-stage renal disease: A systematic review.

Author

Latif AA, Lee KW, Phang K, Rashid AA, Chan NN, Peh SC, Thilaganathan T, and Ooi PB

Abstract

Objectives: This systematic review aims to identify influencing factors of medication adherence behavior in patients with end-stage renal disease (ESRD), with a special interest in patient-related factors based on the World Health Organization adherence model., Materials and Methods: Primary electronic databases comprising PubMed, Scopus, Web of Science, Embase and Cochrane Library, as well as ProQuest (Health and Medical), ProQuest (Psychology), and EBSCOHost (APA PsychARTICLES) were used to search for literature on patient-related factors in medication adherence, from inception till August 31, 2021., Results: 479 articles were identified and six articles meeting eligibility criteria were reviewed and remained in this systematic review. The present review found that despite different tools being used to measure ESRD's perception of medication's necessity and beliefs, there was a profound association between perception and beliefs with medication adherence behavior. There is a positive relationship between knowledge, belief, educational level, ethnicity, female, and medication adherence behavior. Mixed finding was reported between perception, age, and medication adherence behavior. However, there were no studies on patients' attitudes and medication adherence behavior as suggested in the WHO adherence model., Conclusion: Only a limited number of patient-related factors were available for evaluation in the current systematic review. Additional research is needed to advance the understanding of medication adherence behavior affected by patient-related factors on the medication and illness. However, the findings must be taken with caution because of the limited studies included in this review., Competing Interests: There are no conflicts of interest., (Copyright: © 2022 Tzu Chi Medical Journal.)

Published
2022
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44. Development of inactivated heartwater (Ehrlichia ruminantium) vaccine in South Africa.

Author

Molepo LC, Byrom B, Weyers B, Abdelatif N, Mahan SM, Burridge MJ, Barbet AF, and Latif AA

Subjects
Animals, Bacterial Vaccines, Cattle, Mineral Oil, Sheep, South Africa, Ehrlichia ruminantium, Heartwater Disease prevention & control
Abstract

Heartwater, Ehrlichia ruminantium infection in cattle, sheep, goats, and some wild ruminants, is an economically important disease in Africa characterized by high mortality rates in susceptible populations. In South Africa, the current commercial heartwater vaccine is an infection and treatment type of immunization using virulent live E. ruminantium organisms generated from blood of infected sheep with subsequent treatment of the animals with antibiotics at specific times during the course of infection. This vaccine has several inherent problems preventing its wide use as the vaccine must be administered intravenously and it does not protect against all the South African field isolates. A vaccine based on inactivation of Zimbabwean E. ruminantium Mbizi strain organisms produced in endothelial cell cultures can be a sustainable option because it will not require antibiotic treatment and will be safe as there is no potential for reversion to virulence. Previous data generated in laboratory trials and under natural field setting provides support for this vaccine approach. Four inactivated vaccine formulations using the E. ruminantium Mbizi strain were tested for their efficacy in Merino sheep compared to an unvaccinated control group (11 sheep per group). Two vaccines were prepared by beta-propiolactone (BPL) inactivation, and two were inactivated with binary ethylenimine (BEI) while purification was done with both percoll and polyethylene glycol (PEG). The four vaccine preparations were formulated with Montanide ISA 50V2 adjuvant and administered twice subcutaneously (2 ml per dose) at an interval of 4 weeks. All groups were challenged with a virulent homologous cell-cultured E. ruminantium inoculated via the intra-venous route on day 56. The primary variable of efficacy was measured by the percentage survival rate or mortality between the Controls and Vaccine Groups. Three vaccine formulations (BEI/Percoll (Group 3), BEI/PEG (Group 4), BPL/Percoll, (Group 1) had a significantly higher percent of animal surviving challenge compared to the unvaccinated control (p-values 0.001, 0.035, 0.030, respectively). The highest number of survivors was obtained in Group 3 BEI/Percoll; 10/11 (91%). Groups 4 (BEI/PEG) and Group 1 (BPL/Percoll) produced similar percentage of survivals of 64%. In contrast, the lowest survival rate of 50% was observed in Group 2 (BPL/PEG) which was numerically different but not significantly different from the unvaccinated control which had an 18% survival rate (2/11). The inactivated vaccine using BEI or BPL as inactivating agents blended with ISA 50 adjuvant induced protective immunity against challenge. The BEI/Percoll (Group 3) vaccination regimen was most efficacious against a lethal heartwater challenge as it significantly protected sheep against mortality which is the most important aspect of heartwater infections. Future work should be directed towards improvement of this vaccine formulation especially from the down-stream processing point of view as the percoll method is not scalable for commercialization purposes., (Copyright © 2022 Elsevier GmbH. All rights reserved.)

Published
2022
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45. Location and Time Aware Multitask Allocation in Mobile Crowd-Sensing Based on Genetic Algorithm.

Author

Ipaye AA, Chen Z, Asim M, Chelloug SA, Guo L, Ibrahim AMA, and Abd El-Latif AA

Subjects
Group Processes, Humans, Remote Sensing Technology, Algorithms
Abstract

Mobile crowd-sensing (MCS) is a well-known paradigm used for obtaining sensed data by using sensors found in smart devices. With the rise of more sensing tasks and workers in the MCS system, it is now essential to design an efficient approach for task allocation. Moreover, to ensure the completion of the tasks, it is necessary to incentivise the workers by rewarding them for participating in performing the sensing tasks. In this paper, we aim to assist workers in selecting multiple tasks while considering the time constraint of the worker and the requirements of the task. Furthermore, a pricing mechanism is adopted to determine each task budget, which is then used to determine the payment for the workers based on their willingness factor. This paper proves that the task-allocation is a non-deterministic polynomial (NP)-complete problem, which is difficult to solve by conventional optimization techniques. A worker multitask allocation-genetic algorithm (WMTA-GA) is proposed to solve this problem to maximize the workers welfare. Finally, theoretical analysis demonstrates the effectiveness of the proposed WMTA-GA. We observed that it performs better than the state-of-the-art algorithms in terms of average performance, workers welfare, and the number of assigned tasks.

Published
2022
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46. Efficient multimodal deep-learning-based COVID-19 diagnostic system for noisy and corrupted images.

Author

Hammad M, Tawalbeh L, Iliyasu AM, Sedik A, Abd El-Samie FE, Alkinani MH, and Abd El-Latif AA

Abstract

Introduction: In humanity's ongoing fight against its common enemy of COVID-19, researchers have been relentless in finding efficient technologies to support mitigation, diagnosis, management, contact tracing, and ultimately vaccination., Objectives: Engineers and computer scientists have deployed the potent properties of deep learning models (DLMs) in COVID-19 detection and diagnosis. However, publicly available datasets are often adulterated during collation, transmission, or storage. Meanwhile, inadequate, and corrupted data are known to impact the learnability and efficiency of DLMs., Methods: This study focuses on enhancing previous efforts via two multimodal diagnostic systems to extract required features for COVID-19 detection using adulterated chest X-ray images. Our proposed DLM consists of a hierarchy of convolutional and pooling layers that are combined to support efficient COVID-19 detection using chest X-ray images. Additionally, a batch normalization layer is used to curtail overfitting that usually arises from the convolution and pooling (CP) layers., Results: In addition to matching the performance of standard techniques reported in the literature, our proposed diagnostic systems attain an average accuracy of 98% in the detection of normal, COVID-19, and viral pneumonia cases using corrupted and noisy images., Conclusions: Such robustness is crucial for real-world applications where data is usually unavailable, corrupted, or adulterated., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)

Published
2022
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47. Multimedia Cryptosystem for IoT Applications Based on a Novel Chaotic System around a Predefined Manifold.

Author

Li L, Abd El-Latif AA, Jafari S, Rajagopal K, Nazarimehr F, and Abd-El-Atty B

Subjects
Confidentiality, Multimedia, Reproducibility of Results, Algorithms, Computer Security
Abstract

Multimedia data play an important role in our daily lives. The evolution of internet technologies means that multimedia data can easily participate amongst various users for specific purposes, in which multimedia data confidentiality and integrity have serious security issues. Chaos models play an important role in designing robust multimedia data cryptosystems. In this paper, a novel chaotic oscillator is presented. The oscillator has a particular property in which the chaotic dynamics are around pre-located manifolds. Various dynamics of the oscillator are studied. After analyzing the complex dynamics of the oscillator, it is applied to designing a new image cryptosystem, in which the results of the presented cryptosystem are tested from various viewpoints such as randomness, time encryption, correlation, plain image sensitivity, key-space, key sensitivity, histogram, entropy, resistance to classical types of attacks, and data loss analyses. The goal of the paper is proposing an applicable encryption method based on a novel chaotic oscillator with an attractor around a pre-located manifold. All the investigations confirm the reliability of using the presented cryptosystem for various IoT applications from image capture to use it.

Published
2022
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48. Efficient deep learning approach for augmented detection of Coronavirus disease.

Author

Sedik A, Hammad M, Abd El-Samie FE, Gupta BB, and Abd El-Latif AA

Abstract

The new Coronavirus disease 2019 (COVID-19) is rapidly affecting the world population with statistics quickly falling out of date. Due to the limited availability of annotated Coronavirus X-ray and CT images, the detection of COVID-19 remains the biggest challenge in diagnosing this disease. This paper provides a promising solution by proposing a COVID-19 detection system based on deep learning. The proposed deep learning modalities are based on convolutional neural network (CNN) and convolutional long short-term memory (ConvLSTM). Two different datasets are adopted for the simulation of the proposed modalities. The first dataset includes a set of CT images, while the second dataset includes a set of X-ray images. Both of these datasets consist of two categories: COVID-19 and normal. In addition, COVID-19 and pneumonia image categories are classified in order to validate the proposed modalities. The proposed deep learning modalities are tested on both X-ray and CT images as well as a combined dataset that includes both types of images. They achieved an accuracy of 100% and an F1 score of 100% in some cases. The simulation results reveal that the proposed deep learning modalities can be considered and adopted for quick COVID-19 screening., Competing Interests: Conflict of interestNone., (© Springer-Verlag London Ltd., part of Springer Nature 2021.)

Published
2022
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49. An Integrated  Approach for Cancer Survival Prediction Using Data Mining Techniques.

Author

Kaur I, Doja MN, Ahmad T, Ahmad M, Hussain A, Nadeem A, and Abd El-Latif AA

Subjects
Algorithms, Female, Humans, Machine Learning, Data Mining, Neoplasms
Abstract

Ovarian cancer is the third most common gynecologic cancers worldwide. Advanced ovarian cancer patients bear a significant mortality rate. Survival estimation is essential for clinicians and patients to understand better and tolerate future outcomes. The present study intends to investigate different survival predictors available for cancer prognosis using data mining techniques. Dataset of 140 advanced ovarian cancer patients containing data from different data profiles (clinical, treatment, and overall life quality) has been collected and used to foresee cancer patients' survival. Attributes from each data profile have been processed accordingly. Clinical data has been prepared corresponding to missing values and outliers. Treatment data including varying time periods were created using sequence mining techniques to identify the treatments given to the patients. And lastly, different comorbidities were combined into a single factor by computing Charlson Comorbidity Index for each patient. After appropriate preprocessing, the integrated dataset is classified using appropriate machine learning algorithms. The proposed integrated model approach gave the highest accuracy of 76.4% using ensemble technique with sequential pattern mining including time intervals of 2 months between treatments. Thus, the treatment sequences and, most importantly, life quality attributes significantly contribute to the survival prediction of cancer patients., Competing Interests: The authors declare that they have no conflicts of interest., (Copyright © 2021 Ishleen Kaur et al.)

Published
2021
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50. Analysis of the growth performance, stress, profile of fatty acids and amino acids and cortisol in Tilapia ( Oreochromis niloticus ), cultured at high stocking density using in-pond raceway system.

Author

Fatima S, Komal W, Manzoor F, Latif AA, Liaqat R, Ameen S, and Janjua RS

Abstract

In-pond raceway system technology (IPRS) was introduced in Pakistan in 2019 as solution for sustainable aquaculture approach by effectively increasing production, reducing pollution and facilitating feed and pond management. Fingerlings of GIFT Tilapia ( Oreochromis niloticus ) (n = 16,500 in each raceway, initial weight = 32.00 ± 1.26 g) were stocked in June 2019 in two IPRS raceways (area of each raceway = 220 m 3 ) for 171 days until harvested on November 30, 2019. Fingerlings stocked in traditional earthen ponds (area of each pond = 6167 m 3 ) were studied as control (n = 3000 in each pond, initial weight = 32.00 ± 1.26 g). Average harvested biomass from raceways was 57.33 kg/m 3 with an average daily weight gain per fish of 4.47 g per day. On the other hand, average harvested biomass from control ponds was 0.38 kg/m 3 with an average daily weight gain per fish of 4.60 g per day. Average feed conversion ratio (FCR) in both raceways and control ponds was recorded as 1.25 and 1.24, respectively. Overall survival rate in both raceways and control ponds was above 99%. No sign of any disease was noted at any stage in both study groups. Crude protein and fats contents did not reduce in any raceway despite of high stocking density and sharp seasonal changes. Profile of essential and non-essential amino acids were found to be upto nutritional requirements of adult human. High levels of n-3 and n-6 fatty acids in fish collected from raceways as compared to those in traditional earthen pond show that muscle quality was not compromised due to high stocking density in small area. Return on investment excluding capital cost was 47.05 which implies that IPRS technology can be economically feasible with further modifications., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2021 The Author(s).)

Published
2021
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