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115 results on '"Musah, Anwar"'

1. Sex-specific association of ambient temperature with urine biomarkers in Southwest Coastal Bangladesh

Author

Mazumder, Hoimonty, Mondol, Momenul Haque, Rahman, Mahbubur, Khan, Rizwana, Doza, Solaiman, Unicomb, Leanne, Jahan, Farjana, Mukhopadhyay, Ayesha, Makris, Konstantinos, Caban-Martinez, Alberto, Iqbal, Romaina, Ahmed, Faruk, Creencia, Lota, Shamsudduha, Mohammad, Mzayek, Fawaz, Jia, Chunrong, Zhang, Hongmei, Musah, Anwar, Fleming, Lora E, Mou, Xichen, Kovesdy, Csaba P, Gribble, Matthew O, and Abu Mohd Naser

Subjects
Epidemiology, Health Sciences, Clinical Research, Good Health and Well Being, Biomedical and clinical sciences, Health sciences
Published
2024

4. Gamified antimicrobial decision support app (GADSA) changes antibiotics prescription behaviour in surgeons in Nigeria: a hospital-based pilot study

Author

Luedtke, Susanne, Wood, Caroline, Olufemi, Olajumoke, Okonji, Patrick, Kpokiri, Eneyi E., Musah, Anwar, Bammeke, Funmi, Mutiu, Bamidele, Ojewola, Rufus, Bankole, Olufemi, Ademuyiwa, Adesoji, Ekumankama, Chibuzo, Theophilus, Ayibanoah, Aworabhi-Oki, Neni, Shallcross, Laura, Molnar, Andreea, Wiseman, Sue, Hayward, Andrew, Birjovanu, Georgiana, Lefevre, Carmen, Petrou, Stylianos, Ogunsola, Folasade, and Kostkova, Patty

Published
2023
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6. Intelligent Systems for Dengue, Chikungunya, and Zika Temporal and Spatio-Temporal Forecasting: A Contribution and a Brief Review

Author

de Lima, Clarisse Lins, da Silva, Ana Clara Gomes, da Silva, Cecilia Cordeiro, Moreno, Giselle Machado Magalhães, da Silva Filho, Abel Guilhermino, Musah, Anwar, Aldosery, Aisha, Dutra, Livia, Ambrizzi, Tercio, Graciano Borges, Iuri Valério, Tunali, Merve, Basibuyuk, Selma, Yenigün, Orhan, Massoni, Tiago Lima, Jones, Kate, Campos, Luiza, Kostkova, Patty, dos Santos, Wellington P., Pani, Subhendu Kumar, editor, Dash, Sujata, editor, dos Santos, Wellington P., editor, Chan Bukhari, Syed Ahmad, editor, and Flammini, Francesco, editor

Published
2022
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7. Machine Learning Approaches for Temporal and Spatio-Temporal Covid-19 Forecasting: A Brief Review and a Contribution

Author

da Silva, Ana Clara Gomes, de Lima, Clarisse Lins, da Silva, Cecilia Cordeiro, Moreno, Giselle Machado Magalhães, Silva, Eduardo Luiz, Marques, Gabriel Souza, de Araújo, Lucas Job Brito, Júnior, Luiz Antônio Albuquerque, de Souza, Samuel Barbosa Jatobá, de Santana, Maíra Araújo, Gomes, Juliana Carneiro, de Freitas Barbosa, Valter Augusto, Musah, Anwar, Kostkova, Patty, da Silva Filho, Abel Guilhermino, dos Santos, Wellington P., Pani, Subhendu Kumar, editor, Dash, Sujata, editor, dos Santos, Wellington P., editor, Chan Bukhari, Syed Ahmad, editor, and Flammini, Francesco, editor

Published
2022
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8. Spatiotemporal forecasting for dengue, chikungunya fever and Zika using machine learning and artificial expert committees based on meta-heuristics

Author

da Silva, Cecilia Cordeiro, de Lima, Clarisse Lins, da Silva, Ana Clara Gomes, Moreno, Giselle Machado Magalhães, Musah, Anwar, Aldosery, Aisha, Dutra, Livia, Ambrizzi, Tercio, Borges, Iuri V. G., Tunali, Merve, Basibuyuk, Selma, Yenigün, Orhan, Massoni, Tiago Lima, Jones, Kate, Campos, Luiza, Kostkova, Patty, da Silva Filho, Abel Guilhermino, and dos Santos, Wellington Pinheiro

Published
2022
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10. A review exploring the overarching burden of Zika virus with emphasis on epidemiological case studies from Brazil

Author

Tunali, Merve, Radin, Alexandro André, Başıbüyük, Selma, Musah, Anwar, Borges, Iuri Valerio Graciano, Yenigun, Orhan, Aldosery, Aisha, Kostkova, Patty, dos Santos, Wellington P., Massoni, Tiago, Dutra, Livia Marcia Mosso, Moreno, Giselle Machado Magalhaes, de Lima, Clarisse Lins, da Silva, Ana Clara Gomes, Ambrizzi, Tércio, da Rocha, Rosmeri Porfirio, Jones, Kate E., and Campos, Luiza C.

Published
2021
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12. Environmental exposure to metallic soil elements and risk of cancer in the UK population, using a unique linkage between THIN and BGS databases

Author

Musah, Anwar

Subjects
615.9, QV Pharmacology
Abstract

Background: There have been many epidemiological studies into the influence of exposure to the most toxic elements on the risk of cancer in the workplace, mainly due to the exposure of certain occupational groups, or perhaps in populations near industrial sources. Toxic elements include arsenic, copper, nickel, and uranium; and many more of these elements have been shown to increase the risk of several different types of cancers in these highly-exposed groups. Many of these elements naturally exist in the soil, and the health impact of these levels of environmental exposures on the general population has received little attention to date possibly due to the belief that soil concentrations of these elements are too low to cause harm to the general population. Therefore, the long-term effect of such chronic exposure to metals in the soil remains unclear. Aims and objectives: The goals are to utilise a new resource known as THIN-GBASE for conducting a series of environmental epidemiological studies to test the hypothesis that BCC, lung and GIT cancers are associated with high exposure to certain low-level metals in soil. We sought to use this resource in determining which soil metals should be tested for predicting each of the cancer outcomes. Methods: For BCC, an ecological study was initially undertaken to assess the overall regional variation in BCC to provide national and contemporary breakdowns of incidence rates across the UK. The primary exposure of interest for BCC was low-level soil arsenic, and we therefore quantified soil arsenic exposure levels based on the UK national safety limits for arsenic [i.e. As-C4SLs = 35 mg/kg]. A population-based cohort study was conducted to quantify the risks associated between the development of BCC and increasing levels of exposure to soil arsenic. For lung cancer, a two-stage process was adopted: 1) data mining analysis using the correlation-based filter selection model was used to find the restricted set of soil metals were best predictors for lung cancer; and 2) a prospective cohort study was use where these sets of elements were fitted together (adjusted for confounding variables) in a multivariable Cox proportional-hazards model to determine the risks associated between the development of lung cancer, with increasing levels of exposure to each specific element. For GIT cancers, a three-stage process was adopted: stages 1 and 2 used a similar methodology for the lung cancer study. In stage 3, all GIT cancers were divided into three broader outcomes i.e. upper GIT (includes mouth & oesophagus), stomach (as standalone) and colorectal (includes small, large, rectum and anal canal) cancers. A multivariate competing risk survival model was adjusted for the three different GIT cancers as competing events to identify associations between any of the selected group of metals found in stage 1 and GIT-specific cancers. Results: For BCC, the findings for the ecological study show that overall EASRs & WASRs for BCC in the UK was 98.6 and 66.9 per 100,000 person-years, respectively. It indicates a large geographical variation in age-sex standardised incidence of BCC with the South East having the highest incidence of BCC (202.7/100,000 person-years), followed by South Central (193.5/100,000 person-years) and Wales (185.7/100,000 person-years). Incidence rates of BCC were substantially higher in the least socioeconomically deprived groups. It was observed that increasing levels of deprivation led to a decreased rate of BCC (p < 0.001). In terms of age groups, the largest annual increase was observed among those aged 30-49 years. Assessment for soil arsenic indicated that individuals living in areas with concentrations ≥35mg/kg significantly had an increased hazard of developing BCC (35-70mg/kg: adjusted HR 1.08, 95% CI: 1.02-1.14; ≥70mg/kg: adjusted HR 1.17, 95% CI: 1.09-1.28). Urban residents with the highest exposure of soil arsenic had the greatest risk of developing BCC (≥ 70.0 mg/kg: HR 1.18, 95% CI: 1.06-1.36). For lung cancer, the correlation-based filter selection model identified aluminium, lead and uranium as the appropriate set of exposures for modelling lung cancer risk. Complete adjustments of hazards model showed evidence of an increased risk of developing lung cancer with elevated concentrations for only soil aluminium at medium levels ranging between 47,000-61,600mg/kg. Urban residents with the highest exposure of soil aluminium had the greatest risk of developing lung cancer (≥ 61,600mg/kg: HR 1.12, 95% CI: 1.04-1.22). For GIT cancers, the correlation-based filter selection model identified seven elements i.e. aluminium, phosphorus, zinc, uranium, calcium, manganese, and lead, as the appropriate set of exposures for predicting GIT cancer risk. The complete adjustment for hazards model indicated that the risk of developing overall GIT cancers were significantly associated with elevated exposure levels of soil phosphorus only (873-1,127mg/kg: HR 1.08, 95% CI: 1.02-1.14; 1,127-1,456mg/kg: HR 1.07, 95% CI: 1.01-1.13; and ≥1,145mg/kg: HR 1.07, 95% CI: 1.01-1.13). There were no consistent relationships identified between any of the selected groups of elements and the GIT-specific cancer outcomes when adjusting for different GIT cancers as competing events. Conclusion: There appears to be slight evidence of BCC, respiratory and GIT cancer risk with elevated exposure to soil arsenic, aluminium and phosphorus, respectively. The series of investigations conducted for this research are one of the first, if not, contemporary UK-based study to present novel estimates for a group of ill-defined pollutants. This research demonstrates that linking geochemical data with electronic primary care medical records can be a valuable approach of proving whether long term exposure to low-level soil contaminants may have a health consequence in the population.

Published
2017

14. Intelligent Systems for Dengue, Chikungunya, and Zika Temporal and Spatio-Temporal Forecasting: A Contribution and a Brief Review

Author

de Lima, Clarisse Lins, primary, da Silva, Ana Clara Gomes, additional, da Silva, Cecilia Cordeiro, additional, Moreno, Giselle Machado Magalhães, additional, da Silva Filho, Abel Guilhermino, additional, Musah, Anwar, additional, Aldosery, Aisha, additional, Dutra, Livia, additional, Ambrizzi, Tercio, additional, Graciano Borges, Iuri Valério, additional, Tunali, Merve, additional, Basibuyuk, Selma, additional, Yenigün, Orhan, additional, Massoni, Tiago Lima, additional, Jones, Kate, additional, Campos, Luiza, additional, Kostkova, Patty, additional, and dos Santos, Wellington P., additional

Published
2021
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15. Machine Learning Approaches for Temporal and Spatio-Temporal Covid-19 Forecasting: A Brief Review and a Contribution

Author

da Silva, Ana Clara Gomes, primary, de Lima, Clarisse Lins, additional, da Silva, Cecilia Cordeiro, additional, Moreno, Giselle Machado Magalhães, additional, Silva, Eduardo Luiz, additional, Marques, Gabriel Souza, additional, de Araújo, Lucas Job Brito, additional, Júnior, Luiz Antônio Albuquerque, additional, de Souza, Samuel Barbosa Jatobá, additional, de Santana, Maíra Araújo, additional, Gomes, Juliana Carneiro, additional, de Freitas Barbosa, Valter Augusto, additional, Musah, Anwar, additional, Kostkova, Patty, additional, da Silva Filho, Abel Guilhermino, additional, and dos Santos, Wellington P., additional

Published
2021
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16. Gamified Antimicrobial Decision Support App (GADSA) changes antibiotics prescription behaviour in surgeons in Nigeria: A hospital-based pilot study

Author

Luedtke, Susanne, primary, Wood, Caroline, additional, Olufemi, Olajumoke, additional, Okonji, Patrick, additional, Kpokiri, Eneyi E, additional, Musah, Anwar, additional, Bammeke, Funmi, additional, Mutiu, Bamidele, additional, Ojewola, Rufus, additional, Bankole, Olufemi, additional, Ademuyiwa, Adesoji, additional, Ekumankama, Chibuzo, additional, Theophilus, Ayibanoah, additional, Aworabhi-Oki, Neni, additional, Shallcross, Laura, additional, Molnar, Andreea, additional, Wiseman, Sue, additional, Hayward, Andrew, additional, Birjovanu, Georgiana, additional, Lefevre, Carmen, additional, Petrou, Stylianos, additional, Ogunsola, Folasade, additional, and Kostkova, Patty, additional

Published
2023
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18. Coalescing disparate data sources for the geospatial prediction of mosquito abundance, using Brazil as a motivating case study

Author

Musah, Anwar, primary, Browning, Ella, additional, Aldosery, Aisha, additional, Valerio Graciano Borges, Iuri, additional, Ambrizzi, Tercio, additional, Tunali, Merve, additional, Başibüyük, Selma, additional, Yenigün, Orhan, additional, Moreno, Giselle Machado Magalhaes, additional, de Lima, Clarisse Lins, additional, da Silva, Ana Clara Gomes, additional, dos Santos, Wellington Pinheiro, additional, Massoni, Tiago, additional, Campos, Luiza Cintra, additional, and Kostkova, Patty, additional

Published
2023
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20. Descriptive epidemiology of cholera outbreak in Nigeria, January–November, 2018: implications for the global roadmap strategy

Author

Elimian, Kelly Osezele, Musah, Anwar, Mezue, Somto, Oyebanji, Oyeronke, Yennan, Sebastian, Jinadu, Arisekola, Williams, Nanpring, Ogunleye, Adesola, Fall, Ibrahima Soce, Yao, Michel, Eteng, Womi-Eteng, Abok, Patrick, Popoola, Michael, Chukwuji, Martin, Omar, Linda Haj, Ekeng, Eme, Balde, Thieno, Mamadu, Ibrahim, Adeyemo, Ayodele, Namara, Geoffrey, Okudo, Ifeanyi, Alemu, Wondimagegnehu, Peter, Clement, and Ihekweazu, Chikwe

Published
2019
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23. Epidemiology, diagnostics and factors associated with mortality during a cholera epidemic in Nigeria, October 2020–October 2021: a retrospective analysis of national surveillance data

Author

Elimian, Kelly, primary, Yennan, Sebastian, additional, Musah, Anwar, additional, Cheshi, Iliya Danladi, additional, King, Carina, additional, Dunkwu, Lauryn, additional, Mohammed, Ahmed Ladan, additional, Ekeng, Eme, additional, Akande, Oluwatosin Wuraola, additional, Ayres, Stephanie, additional, Gandi, Benjamin, additional, Pembi, Emmanuel, additional, Saleh, Fatima, additional, Omar, Ahmed Nasir, additional, Crawford, Emily, additional, Olopha, Olubunmi Omowumi, additional, Nnaji, Robinson, additional, Muhammad, Basheer, additional, Luka-Lawal, Rejoice, additional, Ihueze, Adachioma Chinonso, additional, Olatunji, David, additional, Ojukwu, Chidimma, additional, Akinpelu, Afolabi Muftau, additional, Adaga, Ene, additional, Abubakar, Yusuf, additional, Nwadiuto, Ifeoma, additional, Ngishe, Samuel, additional, Alowooye, Agnes Bosede, additional, Nwogwugwu, Peace Chinma, additional, Kamaldeen, Khadeejah, additional, Abah, Henry Nweke, additional, Chukwuebuka, Egbuna Hyacinth, additional, Yusuff, Hakeem Abiola, additional, Mamadu, Ibrahim, additional, Mohammed, Abbas Aliyu, additional, Peter, Sarah, additional, Abbah, Okpachi Christopher, additional, Oladotun, Popoola Michael, additional, Oifoh, Santino, additional, Olugbile, Micheal, additional, Agogo, Emmanuel, additional, Ndodo, Nnaemeka, additional, Babatunde, Olajumoke, additional, Mba, Nwando, additional, Oladejo, John, additional, Ilori, Elsie, additional, Alfvén, Tobias, additional, Myles, Puja, additional, Ochu, Chinwe Lucia, additional, Ihekweazu, Chikwe, additional, and Adetifa, Ifedayo, additional

Published
2022
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24. An Evaluation of the OpenWeatherMap API versus INMET Using Weather Data from Two Brazilian Cities: Recife and Campina Grande

Author

Musah, Anwar, primary, Dutra, Livia Màrcia Mosso, additional, Aldosery, Aisha, additional, Browning, Ella, additional, Ambrizzi, Tercio, additional, Borges, Iuri Valerio Graciano, additional, Tunali, Merve, additional, Başibüyük, Selma, additional, Yenigün, Orhan, additional, Moreno, Giselle Machado Magalhaes, additional, da Silva, Ana Clara Gomes, additional, dos Santos, Wellington Pinheiro, additional, de Lima, Clarisse Lins, additional, Massoni, Tiago, additional, Jones, Kate Elizabeth, additional, Campos, Luiza Cintra, additional, and Kostkova, Patty, additional

Published
2022
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27. COVID-19 mortality rate and its associated factors during the first and second waves in Nigeria

Author

Elimian, Kelly, primary, Musah, Anwar, additional, King, Carina, additional, Igumbor, Ehimario, additional, Myles, Puja, additional, Aderinola, Olaolu, additional, Erameh, Cyril, additional, Nwanchukwu, William, additional, Akande, Oluwatosin, additional, Nicaise, Ndembi, additional, Ogunbode, Oladipo, additional, Egwuenu, Abiodun, additional, Crawford, Emily, additional, Gaudenzi, Giulia, additional, Abdus-Salam, Ismail, additional, Olopha, Olubunmi, additional, Disu, Yahya, additional, Bowale, Abimbola, additional, Oshoma, Cyprian, additional, Ohonsi, Cornelius, additional, Arinze, Chinedu, additional, Badaru, Sikiru, additional, Ebhodaghe, Blessing, additional, Habib, Zaiyad, additional, Olugbile, Michael, additional, Dan-Nwafor, Chioma, additional, Abubakar, Jafiya, additional, Pembi, Emmanuel, additional, Dunkwu, Lauryn, additional, Ike, Ifeanyi, additional, Tobin, Ekaete, additional, Mutiu, Bamidele, additional, Luka-Lawal, Rejoice, additional, Nwafor, Obinna, additional, Okowa, Mildred, additional, Ezeokafor, Chidiebere, additional, Iwara, Emem, additional, Yennan, Sebastian, additional, Eziechina, Sunday, additional, Olatunji, David, additional, Falodun, Lanre, additional, Joseph, Emmanuel, additional, Abali, Ifeanyi, additional, Mohammed, Tarik, additional, Yiga, Benjamin, additional, Kamaldeen, Khadeejah, additional, Agogo, Emmanuel, additional, Mba, Nwando, additional, Oladejo, John, additional, Ilori, Elsie, additional, Aruna, Olusola, additional, Namara, Geoffrey, additional, Obaro, Stephen, additional, Hamza, Khadeejah, additional, Asuzu, Michael, additional, Bello, Shaibu, additional, Okonofua, Friday, additional, Deeni, Yusuf, additional, Abubakar, Ibrahim, additional, Alfven, Tobias, additional, Ochu, Chinwe, additional, and Ihekweazu, Chikwe, additional

Published
2022
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28. Temporal and Spatiotemporal Arboviruses Forecasting by Machine Learning: A Systematic Review

Author

Lima, Clarisse Lins de, primary, da Silva, Ana Clara Gomes, additional, Moreno, Giselle Machado Magalhães, additional, Cordeiro da Silva, Cecilia, additional, Musah, Anwar, additional, Aldosery, Aisha, additional, Dutra, Livia, additional, Ambrizzi, Tercio, additional, Borges, Iuri V. G., additional, Tunali, Merve, additional, Basibuyuk, Selma, additional, Yenigün, Orhan, additional, Massoni, Tiago Lima, additional, Browning, Ella, additional, Jones, Kate, additional, Campos, Luiza, additional, Kostkova, Patty, additional, Silva Filho, Abel Guilhermino da, additional, and dos Santos, Wellington Pinheiro, additional

Published
2022
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29. Prediction of Aedes aegypti breeding distribution through spatiotemporal analysis and machine learning: A case study in Recife, Pernambuco

Author

de Lima, Clarisse Lins, primary, Silva, Cecilia Cordeiro da, additional, Silva, Ana Clara Gomes da, additional, Silva, Aracely Andrade da, additional, de Almeida, Felipe Rodrigues, additional, de Gusmão, Cristine Martins Gomes, additional, Moreno, Giselle Machado Magalhães, additional, Musah, Anwar, additional, Aldosery, Aisha, additional, Browning, Ella, additional, Dutra, Livia, additional, Ambrizzi, Tercio, additional, Borges, Iuri V. G., additional, Tunali, Merve, additional, Basibuyuk, Selma, additional, Yenigün, Orhan, additional, Massoni, Tiago Lima, additional, Jones, Kate, additional, Campos, Luiza C., additional, Kostkova, Patty, additional, Filho, Abel Guilhermino da Silva, additional, and Santos, Wellington Pinheiro dos, additional

Published
2022
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30. Exploring barriers to guideline implementation for prescription of surgical antibiotic prophylaxis in Nigeria

Author

Wood, Caroline E., primary, Luedtke, Susanne, additional, Musah, Anwar, additional, Bammeke, Funmi, additional, Mutiu, Bamidele, additional, Ojewola, Rufus, additional, Bankole, Olufemi, additional, Ademuyiwa, Adesoji Oludotun, additional, Ekumankama, Chibuzo Barbara, additional, Ogunsola, Folasade, additional, Okonji, Patrick, additional, Kpokiri, Eneyi E., additional, Ayibanoah, Theophilus, additional, Aworabhi-Oki, Neni, additional, Shallcross, Laura, additional, Molnar, Andreea, additional, Wiseman, Sue, additional, Hayward, Andrew, additional, Soriano, Delphine, additional, Birjovanu, Georgiana, additional, Lefevre, Carmen, additional, Olufemi, Olajumoke, additional, and Kostkova, Patty, additional

Published
2022
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31. MEWAR: Development of a Cross-Platform Mobile Application and Web Dashboard System for Real-Time Mosquito Surveillance in Northeast Brazil

Author

Aldosery, Aisha, primary, Musah, Anwar, additional, Birjovanu, Georgiana, additional, Moreno, Giselle, additional, Boscor, Andrei, additional, Dutra, Livia, additional, Santos, George, additional, Nunes, Vania, additional, Oliveira, Rossandra, additional, Ambrizzi, Tercio, additional, Massoni, Tiago, additional, dos Santos, Wellington Pinheiro, additional, and Kostkova, Patty, additional

Published
2021
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32. Forecasting Dengue, Chikungunya and Zika cases in Recife, Brazil: a spatio-temporal approach based on climate conditions, health notifications and machine learning

Author

Silva, Cecilia Cordeiro da, primary, Lima, Clarisse Lins de, additional, Silva, Ana Clara Gomes da, additional, Moreno, Giselle Machado Magalhães, additional, Musah, Anwar, additional, Aldosery, Aisha, additional, Dutra, Livia, additional, Ambrizzi, Tercio, additional, Borges, Iuri Valério Graciano, additional, Tunali, Merve, additional, Basibuyuk, Selma, additional, Yenigün, Orhan, additional, Jones, Kate, additional, Campos, Luiza, additional, Massoni, Tiago Lima, additional, Silva Filho, Abel Guilhermino da, additional, Kostkova, Patty, additional, and Santos, Wellington Pinheiro dos, additional

Published
2021
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33. Covid-19 Dynamic Monitoring and Real-Time Spatio-Temporal Forecasting

Author

da Silva, Cecilia Cordeiro, primary, de Lima, Clarisse Lins, additional, da Silva, Ana Clara Gomes, additional, Silva, Eduardo Luiz, additional, Marques, Gabriel Souza, additional, de Araújo, Lucas Job Brito, additional, Albuquerque Júnior, Luiz Antônio, additional, de Souza, Samuel Barbosa Jatobá, additional, de Santana, Maíra Araújo, additional, Gomes, Juliana Carneiro, additional, Barbosa, Valter Augusto de Freitas, additional, Musah, Anwar, additional, Kostkova, Patty, additional, dos Santos, Wellington Pinheiro, additional, and da Silva Filho, Abel Guilhermino, additional

Published
2021
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35. Incidence Rate of COVID-19 Mortality and its Associated Factors During the First and Second Waves in Nigeria: A Retrospective Cohort Study

Author

Elimian, Kelly, primary, Musah, Anwar, additional, King, Carina, additional, Igumbor, Ehimario, additional, Myles, Puja, additional, Aderinola, Olaolu, additional, Erameh, Cyril, additional, Nwanchukwu, William, additional, Akande, Oluwatosin, additional, Nicaise, Ndembi, additional, Ogunbode, Oladipo, additional, Egwuenu, Abiodun, additional, Crawford, Emily, additional, Gaudenzi, Giulia, additional, Abdus-Salam, Ismail, additional, Olopha, Olubunmi, additional, Disu, Yahya, additional, Bowale, Abimbola, additional, Oshoma, Cyprian, additional, Ohonsi, Cornelius, additional, Arinze, Chinedu, additional, Badaru, Sikiru, additional, Ebhodaghe, Blessing, additional, Habib, Zaiyad, additional, Olugbile, Michael, additional, Dan-Nwafor, Chioma, additional, Abubakar, Jafiya, additional, Pembi, Emmanuel, additional, Dunkwu, Lauryn, additional, Ike, Ifeanyi, additional, Tobin, Ekaete, additional, Mutiu, Bamidele, additional, Luka-Lawal, Rejoice, additional, Nwafor, Obinna, additional, Okowa, Mildred, additional, Ezeokafor, Chidiebere, additional, Iwara, Emem, additional, Yennan, Sebastian, additional, Eziechina, Sunday, additional, Olatunji, David, additional, Falodun, Lanre, additional, Joseph, Emmanuel, additional, Abali, Ifeanyi, additional, Tarik, Mohammed, additional, Yiga, Benjamin, additional, Kamaldeen, Khadeejah, additional, Agogo, Emmanuel, additional, Audu, Rosemary, additional, Olayinka, Adebola, additional, Okunromade, Oyeladun, additional, Mba, Nwando, additional, Oladejo, John, additional, Ilori, Elsie, additional, Aruna, Olusola, additional, Namara, Geoffrey, additional, Obaro, Stephen, additional, Hamza, Khadeejah, additional, Asuzu, Michael, additional, Bello, Shaibu Oricha, additional, Obi, Andrew, additional, Okonofua, Friday, additional, Deeni, Yusuf, additional, Abubakar, Ibrahim, additional, Alfven, Tobias, additional, Ochu, Chinwe, additional, and Ihekweazu, Chikwe, additional

Published
2021
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37. Additional file 2 of What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review

Author

Elimian, Kelly Osezele, Somto Mezue, Musah, Anwar, Oyeronke Oyebanji, Ibrahima Soce Fall, Yennan, Sebastian, Yao, Michel, Abok, Patrick Okumu, Nanpring Williams, Omar, Lynda Haj, Thieno Balde, Kobina Ampah, Ifeanyi Okudo, Ibrahim, Luka, Arisekola Jinadu, Wondimagegnehu Alemu, Peter, Clement, and Chikwe Ihekweazu

Subjects
Data_FILES
Abstract

Additional file 2.

Published
2020
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38. Additional file 1 of What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review

Author

Elimian, Kelly Osezele, Somto Mezue, Musah, Anwar, Oyeronke Oyebanji, Ibrahima Soce Fall, Yennan, Sebastian, Yao, Michel, Abok, Patrick Okumu, Nanpring Williams, Omar, Lynda Haj, Thieno Balde, Kobina Ampah, Ifeanyi Okudo, Ibrahim, Luka, Arisekola Jinadu, Wondimagegnehu Alemu, Peter, Clement, and Chikwe Ihekweazu

Subjects
Data_FILES
Abstract

Additional file 1.

Published
2020
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39. Additional file 3 of What are the drivers of recurrent cholera transmission in Nigeria? Evidence from a scoping review

Author

Elimian, Kelly Osezele, Somto Mezue, Musah, Anwar, Oyeronke Oyebanji, Ibrahima Soce Fall, Yennan, Sebastian, Yao, Michel, Abok, Patrick Okumu, Nanpring Williams, Omar, Lynda Haj, Thieno Balde, Kobina Ampah, Ifeanyi Okudo, Ibrahim, Luka, Arisekola Jinadu, Wondimagegnehu Alemu, Peter, Clement, and Chikwe Ihekweazu

Subjects
Data_FILES
Abstract

Additional file 3.

Published
2020
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40. COVID-SGIS: A Smart Tool for Dynamic Monitoring and Temporal Forecasting of Covid-19

Author

de Lima, Clarisse Lins, primary, da Silva, Cecilia Cordeiro, additional, da Silva, Ana Clara Gomes, additional, Luiz Silva, Eduardo, additional, Marques, Gabriel Souza, additional, de Araújo, Lucas Job Brito, additional, Albuquerque Júnior, Luiz Antônio, additional, de Souza, Samuel Barbosa Jatobá, additional, de Santana, Maíra Araújo, additional, Gomes, Juliana Carneiro, additional, de Freitas Barbosa, Valter Augusto, additional, Musah, Anwar, additional, Kostkova, Patty, additional, dos Santos, Wellington Pinheiro, additional, and da Silva Filho, Abel Guilhermino, additional

Published
2020
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41. Identifying and quantifying the factors associated with cholera-related death during the 2018 outbreak in Nigeria

Author

Elimian, Kelly Osezele, primary, Musah, Anwar, additional, Ochu, Chinwe Lucia, additional, Onwah, Somtochukwu Stella, additional, Oyebanji, Oyeronke, additional, Yennan, Sebastian, additional, Fall, Ibrahima Soce, additional, Yao, Michel, additional, Chukwuji, Martin, additional, Ekeng, Eme, additional, Abok, Patrick, additional, Omar, Linda Haj, additional, Balde, Thieno, additional, Kankia, Adamu, additional, Williams, Nanpring, additional, Mutbam, Kitgakka, additional, Dhamari, Naidoo, additional, Okudo, Ifeanyi, additional, Alemu, Wondimagegnehu, additional, Peter, Clement, additional, and Ihekweazu, Chikwe, additional

Published
2020
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43. ZIKA Virus

Author

Rubio-Solis, Adrian, primary, Musah, Anwar, additional, P. Dos Santos, Wellington, additional, Massoni, Tiago, additional, Birjovanu, Georgiana, additional, and Kostkova, Patty, additional

Published
2019
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44. Additional file 1: of Descriptive epidemiology of cholera outbreak in Nigeria, Januaryâ November, 2018: implications for the global roadmap strategy

Author

Elimian, Kelly, Musah, Anwar, Somto Mezue, Oyeronke Oyebanji, Yennan, Sebastian, Arisekola Jinadu, Nanpring Williams, Adesola Ogunleye, Ibrahima Fall, Yao, Michel, Womi-Eteng Eteng, Abok, Patrick, Popoola, Michael, Chukwuji, Martin, Omar, Linda, Eme Ekeng, Thieno Balde, Mamadu, Ibrahim, Ayodele Adeyemo, Namara, Geoffrey, Ifeanyi Okudo, Wondimagegnehu Alemu, Peter, Clement, and Chikwe Ihekweazu

Abstract

Table showing the age and sex distribution of case fatality rates among cholera cases, Nigeria, 2018. (DOCX 12 kb)

Published
2019
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45. Assessing the impacts of Airbnb listings on London house prices

Author

Todd, James, Musah, Anwar, and Cheshire, James

Abstract

Over the course of the last decade, sharing economy platforms have experienced significant growth within cities around the world. Airbnb, which is one of the largest and best-known platforms, provides the focus for this paper and offers a service that allows users to rent properties or spare rooms to guests. Its rapid growth has led to a growing discourse around the consequences of Airbnb rentals within the local context. The research within this paper focuses on determining impact on local housing prices within the inner London boroughs by constructing a longitudinal panel dataset, on which a fixed and random effects regression was conducted. The results indicate that there is a significant and modest positive association between the frequency of Airbnb and the house price per square metre in these boroughs.

Published
2022
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46. ZIKA Virus.

Author

Rubio-Solis, Adrian, Musah, Anwar, P. Dos Santos, Wellington, Massoni, Tiago, Birjovanu, Georgiana, and Kostkova, Patty

Published
2019
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48. Additional file 2: of Linkage of national soil quality measurements to primary care medical records in England and Wales: a new resource for investigating environmental impacts on human health

Author

Gibson, Jack, E. Ander, Cave, Mark, Bath-Hextall, Fiona, Musah, Anwar, and Leonardi-Bee, Jo

Abstract

Observed range of concentrations of 15 linked constituent elements in the residential soils of patients enrolled in The Health Improvement Network database on the date of the 2011 UK census, by Strategic Health Authority, and comparison with the expected range of concentrations in the residential soils of the entire Strategic Health Authority populations, estimated using 2011 Census population distributions. Boxes indicate interquartile ranges, midlines indicate median values and whiskers are drawn to the upper and lower adjacent values. (PDF 87 kb)

Published
2018
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49. Additional file 1: of Linkage of national soil quality measurements to primary care medical records in England and Wales: a new resource for investigating environmental impacts on human health

Author

Gibson, Jack, E. Ander, Cave, Mark, Bath-Hextall, Fiona, Musah, Anwar, and Leonardi-Bee, Jo

Abstract

Maps of soil element levels by United Kingdom Strategic Health Authority area. Contains Ordnance Survey data Š Crown Copyright and database rights [2015]. (DOCX 33519 kb)

Published
2018
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50. Environmental exposure to metallic soil elements and risk of cancer in the UK population, using a unique linkage between THIN and BGS databases

Author

Musah, Anwar

Abstract

Background: There have been many epidemiological studies into the influence of exposure to the most toxic elements on the risk of cancer in the workplace, mainly due to the exposure of certain occupational groups, or perhaps in populations near industrial sources. Toxic elements include arsenic, copper, nickel, and uranium; and many more of these elements have been shown to increase the risk of several different types of cancers in these highly-exposed groups. Many of these elements naturally exist in the soil, and the health impact of these levels of environmental exposures on the general population has received little attention to date possibly due to the belief that soil concentrations of these elements are too low to cause harm to the general population. Therefore, the long-term effect of such chronic exposure to metals in the soil remains unclear.\ud \ud \ud Aims and objectives: The goals are to utilise a new resource known as THIN-GBASE for conducting a series of environmental epidemiological studies to test the hypothesis that BCC, lung and GIT cancers are associated with high exposure to certain low-level metals in soil. We sought to use this resource in determining which soil metals should be tested for predicting each of the cancer outcomes.\ud \ud \ud Methods: For BCC, an ecological study was initially undertaken to assess the overall regional variation in BCC to provide national and contemporary breakdowns of incidence rates across the UK. The primary exposure of interest for BCC was low-level soil arsenic, and we therefore quantified soil arsenic exposure levels based on the UK national safety limits for arsenic [i.e. As-C4SLs = 35 mg/kg]. A population-based cohort study was conducted to quantify the risks associated between the development of BCC and increasing levels of exposure to soil arsenic. For lung cancer, a two-stage process was adopted: 1) data mining analysis using the correlation-based filter selection model was used to find the restricted set of soil metals were best predictors for lung cancer; and 2) a prospective cohort study was use where these sets of elements were fitted together (adjusted for confounding variables) in a multivariable Cox proportional-hazards model to determine the risks associated between the development of lung cancer, with increasing levels of exposure to each specific element. For GIT cancers, a three-stage process was adopted: stages 1 and 2 used a similar methodology for the lung cancer study. In stage 3, all GIT cancers were divided into three broader outcomes i.e. upper GIT (includes mouth & oesophagus), stomach (as standalone) and colorectal (includes small, large, rectum and anal canal) cancers. A multivariate competing risk survival model was adjusted for the three different GIT cancers as competing events to identify associations between any of the selected group of metals found in stage 1 and GIT-specific cancers. \ud \ud \ud Results: For BCC, the findings for the ecological study show that overall EASRs & WASRs for BCC in the UK was 98.6 and 66.9 per 100,000 person-years, respectively. It indicates a large geographical variation in age-sex standardised incidence of BCC with the South East having the highest incidence of BCC (202.7/100,000 person-years), followed by South Central (193.5/100,000 person-years) and Wales (185.7/100,000 person-years). Incidence rates of BCC were substantially higher in the least socioeconomically deprived groups. It was observed that increasing levels of deprivation led to a decreased rate of BCC (p < 0.001). In terms of age groups, the largest annual increase was observed among those aged 30-49 years. Assessment for soil arsenic indicated that individuals living in areas with concentrations ≥35mg/kg significantly had an increased hazard of developing BCC (35-70mg/kg: adjusted HR 1.08, 95% CI: 1.02-1.14; ≥70mg/kg: adjusted HR 1.17, 95% CI: 1.09-1.28). Urban residents with the highest exposure of soil arsenic had the greatest risk of developing BCC (≥ 70.0 mg/kg: HR 1.18, 95% CI: 1.06-1.36). For lung cancer, the correlation-based filter selection model identified aluminium, lead and uranium as the appropriate set of exposures for modelling lung cancer risk. Complete adjustments of hazards model showed evidence of an increased risk of developing lung cancer with elevated concentrations for only soil aluminium at medium levels ranging between 47,000-61,600mg/kg. Urban residents with the highest exposure of soil aluminium had the greatest risk of developing lung cancer (≥ 61,600mg/kg: HR 1.12, 95% CI: 1.04-1.22). For GIT cancers, the correlation-based filter selection model identified seven elements i.e. aluminium, phosphorus, zinc, uranium, calcium, manganese, and lead, as the appropriate set of exposures for predicting GIT cancer risk. The complete adjustment for hazards model indicated that the risk of developing overall GIT cancers were significantly associated with elevated exposure levels of soil phosphorus only (873-1,127mg/kg: HR 1.08, 95% CI: 1.02-1.14; 1,127-1,456mg/kg: HR 1.07, 95% CI: 1.01-1.13; and ≥1,145mg/kg: HR 1.07, 95% CI: 1.01-1.13). There were no consistent relationships identified between any of the selected groups of elements and the GIT-specific cancer outcomes when adjusting for different GIT cancers as competing events. \ud \ud \ud Conclusion: There appears to be slight evidence of BCC, respiratory and GIT cancer risk with elevated exposure to soil arsenic, aluminium and phosphorus, respectively. The series of investigations conducted for this research are one of the first, if not, contemporary UK-based study to present novel estimates for a group of ill-defined pollutants. This research demonstrates that linking geochemical data with electronic primary care medical records can be a valuable approach of proving whether long term exposure to low-level soil contaminants may have a health consequence in the population.

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