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5 results on '"Monagin, Corina"'

1. Predicting the potential for zoonotic transmission and host associations for novel viruses

Author

Pandit, Pranav S, Anthony, Simon J, Goldstein, Tracey, Olival, Kevin J, Doyle, Megan M, Gardner, Nicole R, Bird, Brian, Smith, Woutrina, Wolking, David, Gilardi, Kirsten, Monagin, Corina, Kelly, Terra, Uhart, Marcela M, Epstein, Jonathan H, Machalaba, Catherine, Rostal, Melinda K, Dawson, Patrick, Hagan, Emily, Sullivan, Ava, Li, Hongying, Chmura, Aleksei A, Latinne, Alice, Lange, Christian, O’Rourke, Tammie, Olson, Sarah, Keatts, Lucy, Mendoza, A Patricia, Perez, Alberto, de Paula, Cátia Dejuste, Zimmerman, Dawn, Valitutto, Marc, LeBreton, Matthew, McIver, David, Islam, Ariful, Duong, Veasna, Mouiche, Moctar, Shi, Zhengli, Mulembakani, Prime, Kumakamba, Charles, Ali, Mohamed, Kebede, Nigatu, Tamoufe, Ubald, Bel-Nono, Samuel, Camara, Alpha, Pamungkas, Joko, Coulibaly, Kalpy J, Abu-Basha, Ehab, Kamau, Joseph, Silithammavong, Soubanh, Desmond, James, Hughes, Tom, Shiilegdamba, Enkhtuvshin, Aung, Ohnmar, Karmacharya, Dibesh, Nziza, Julius, Ndiaye, Daouda, Gbakima, Aiah, Sajali, Zikankuba, Wacharapluesadee, Supaporn, Robles, Erika Alandia, Ssebide, Benard, Suzán, Gerardo, Aguirre, Luis F, Solorio, Monica R, Dhole, Tapan N, Nga, Nguyen TT, Hitchens, Peta L, Joly, Damien O, Saylors, Karen, Fine, Amanda, Murray, Suzan, Karesh, William B, Daszak, Peter, Mazet, Jonna AK, and Johnson, Christine K

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Infectious Diseases, 2.2 Factors relating to the physical environment, 2.1 Biological and endogenous factors, Infection, Africa, Animals, Animals, Wild, Host Specificity, Humans, Viruses, Zoonoses, PREDICT Consortium, Biological sciences, Biomedical and clinical sciences
Abstract

Host-virus associations have co-evolved under ecological and evolutionary selection pressures that shape cross-species transmission and spillover to humans. Observed virus-host associations provide relevant context for newly discovered wildlife viruses to assess knowledge gaps in host-range and estimate pathways for potential human infection. Using models to predict virus-host networks, we predicted the likelihood of humans as hosts for 513 newly discovered viruses detected by large-scale wildlife surveillance at high-risk animal-human interfaces in Africa, Asia, and Latin America. Predictions indicated that novel coronaviruses are likely to infect a greater number of host species than viruses from other families. Our models further characterize novel viruses through prioritization scores and directly inform surveillance targets to identify host ranges for newly discovered viruses.

Published
2022

2. Bridging the gap: Using reservoir ecology and human serosurveys to estimate Lassa virus spillover in West Africa

Author

Basinski, Andrew J, Fichet-Calvet, Elisabeth, Sjodin, Anna R, Varrelman, Tanner J, Remien, Christopher H, Layman, Nathan C, Bird, Brian H, Wolking, David J, Monagin, Corina, Ghersi, Bruno M, Barry, Peter A, Jarvis, Michael A, Gessler, Paul E, and Nuismer, Scott L

Subjects
Climate Change Impacts and Adaptation, Environmental Sciences, Emerging Infectious Diseases, Clinical Research, Infectious Diseases, Prevention, 2.2 Factors relating to the physical environment, Aetiology, Infection, Africa, Western, Animals, Animals, Wild, Computational Biology, Disease Reservoirs, Ecology, Humans, Lassa Fever, Lassa virus, Machine Learning, Models, Biological, Models, Statistical, Risk, Rodentia, Mathematical Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

Forecasting the risk of pathogen spillover from reservoir populations of wild or domestic animals is essential for the effective deployment of interventions such as wildlife vaccination or culling. Due to the sporadic nature of spillover events and limited availability of data, developing and validating robust, spatially explicit, predictions is challenging. Recent efforts have begun to make progress in this direction by capitalizing on machine learning methodologies. An important weakness of existing approaches, however, is that they generally rely on combining human and reservoir infection data during the training process and thus conflate risk attributable to the prevalence of the pathogen in the reservoir population with the risk attributed to the realized rate of spillover into the human population. Because effective planning of interventions requires that these components of risk be disentangled, we developed a multi-layer machine learning framework that separates these processes. Our approach begins by training models to predict the geographic range of the primary reservoir and the subset of this range in which the pathogen occurs. The spillover risk predicted by the product of these reservoir specific models is then fit to data on realized patterns of historical spillover into the human population. The result is a geographically specific spillover risk forecast that can be easily decomposed and used to guide effective intervention. Applying our method to Lassa virus, a zoonotic pathogen that regularly spills over into the human population across West Africa, results in a model that explains a modest but statistically significant portion of geographic variation in historical patterns of spillover. When combined with a mechanistic mathematical model of infection dynamics, our spillover risk model predicts that 897,700 humans are infected by Lassa virus each year across West Africa, with Nigeria accounting for more than half of these human infections.

Published
2021

3. Assessing Climate Change Impact on Ecosystems and Infectious Disease: Important Roles for Genomic Sequencing and a One Health Perspective

Author

Yeh, Kenneth B, Fair, Jeanne M, Smith, Woutrina, Torres, Teresa Martinez, Lucas, Julie, Monagin, Corina, Winegar, Richard, and Fletcher, Jacqueline

Subjects
Climate-Related Exposures and Conditions, Biotechnology, Emerging Infectious Diseases, Infectious Diseases, Vector-Borne Diseases, Prevention, Vaccine Related, 2.2 Factors relating to the physical environment, Aetiology, Infection, Good Health and Well Being, Climate Action, biosecurity, climate change impact, One Health, genome, sequencing, infectious disease
Abstract

Changes in the Earth's climate and weather continue to impact the planet's ecosystems, including the interface of infectious disease agents with their hosts and vectors. Environmental disasters, natural and human-made activities raise risk factors that indirectly facilitate infectious disease outbreaks. Subsequently, changes in habitat, displaced populations, and environmental stresses that affect the survival of species are amplified over time. The recurrence and spread of vector-borne (e.g., mosquito, tick, aphid) human, animal, and plant pathogens to new geographic locations are also influenced by climate change. The distribution and range of humans, agricultural animals and plants, wildlife and native plants, as well as vectors, parasites, and microbes that cause neglected diseases of the tropics as well as other global regions are also impacted. In addition, genomic sequencing can now be applied to detect signatures of infectious pathogens as they move into new regions. Molecular detection assays complement metagenomic sequencing to help us understand the microbial community found within the microbiomes of hosts and vectors, and help us uncover mechanistic relationships between climate variability and pathogen transmission. Our understanding of, and responses to, such complex dynamics and their impacts can be enhanced through effective, multi-sectoral One Health engagement coupled with applications of both traditional and novel technologies. Concerted efforts are needed to further harness and leverage technology that can identify and track these impacts of climate changes in order to mitigate and adapt to their effects.

Published
2020

4. The discovery of Bombali virus adds further support for bats as hosts of ebolaviruses

Author

Goldstein, Tracey, Anthony, Simon J, Gbakima, Aiah, Bird, Brian H, Bangura, James, Tremeau-Bravard, Alexandre, Belaganahalli, Manjunatha N, Wells, Heather L, Dhanota, Jasjeet K, Liang, Eliza, Grodus, Michael, Jangra, Rohit K, DeJesus, Veronica A, Lasso, Gorka, Smith, Brett R, Jambai, Amara, Kamara, Brima O, Kamara, Sorie, Bangura, William, Monagin, Corina, Shapira, Sagi, Johnson, Christine K, Saylors, Karen, Rubin, Edward M, Chandran, Kartik, Lipkin, W Ian, and Mazet, Jonna AK

Subjects
Vaccine Related, Aetiology, 2.2 Factors relating to the physical environment, Infection, Animals, Cell Line, Tumor, Chiroptera, Ebolavirus, Genome, Viral, Humans, Phylogeny, Viral Envelope Proteins, Viral Load, Virus Internalization, Microbiology, Medical Microbiology
Abstract

Here we describe the complete genome of a new ebolavirus, Bombali virus (BOMV) detected in free-tailed bats in Sierra Leone (little free-tailed (Chaerephon pumilus) and Angolan free-tailed (Mops condylurus)). The bats were found roosting inside houses, indicating the potential for human transmission. We show that the viral glycoprotein can mediate entry into human cells. However, further studies are required to investigate whether exposure has actually occurred or if BOMV is pathogenic in humans.

Published
2018

5. Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

Author

Saylors, Karen, Wolking, David J., Hagan, Emily, Martinez, Stephanie, Francisco, Leilani, Euren, Jason, Olson, Sarah H., Miller, Maureen, Fine, Amanda E., Thanh, Nga Nguyen Thi, Tran Minh, Phuc, Kalengkongan, Jusuf D., Kusumaningrum, Tina, Latinne, Alice, Pamungkas, Joko, Safari, Dodi, Saputro, Suryo, Bamba, Djeneba, Coulibaly, Kalpy Julien, Dosso, Mireille, Laudisoit, Anne, N'guettia Jean, Kouassi Manzan, Dutta, Shusmita, Islam, Ariful, Shano, Shahanaj, Mwanzalila, Mwokozi I., Trupin, Ian P., Gbakima, Aiah, Bangura, James, Yondah, Sylvester T., Karmacharya, Dibesh, Shrestha, Rima D., Kamta, Marcelle Annie Matsida, Mouiche, Mohamed Moctar Mouliom, Ndolo, Hilarion Moukala, Niama, Fabien Roch, Onikrotin, Dionne, Daszak, Peter, Johnson, Christine K., Mazet, Jonna A. K., Abaneh, Ola, Ababneh, Mustafa, Rafia, Jum, Sukor, Abd, Abdullah, Mohd Lufti, Abedin, Josefina, Abu-Basha, Ehab, Ali, Mohamed, Beal Akoundze, Junior, Akpaki, Joel, Al Hanandeh, Sief Addeen, Al Omari, Bilal, Al Shakil, Abdullah, Al-Zghoul, Mohammed, Albart, Stephenie Ann, Alshammari, Abdullah, Amarneh, Basil H., Ampofo, William, Andrew, Victoria, Ahn, Dao Le, Ankhanbaatar, Ulaankhuu, Anthony, Simon, Antonjaya, Ungke, Araya, Kidan, Arku, Jallah, Arshat, Norsharina, Asigbee, Theodore, Aung, Ohnmar, Awuni, Joseph, Ayukebong, James, Azian, Mohammed, Aziz, Nor Adilah, Ba, Aminata, Bassan, Ganzorig, Bagato, Ola, Bamba, Aboubacar, Bamba, Djenba, Barkhasbaatar, Ariunbaatar, Barrera, June, Basaraba, Cale, Bel-nono, Samuel, Belaganahalli, Manjunatha, Belay, Desalgen, Belkharia, Jaber, Binol, Ridzki M. F., Bird, Brian, Bista, Manisha, Biswas, Pitu, Blake, Matthew, Boatemaa, Linda, Bonason, Margret, Brandful, James, Brown, Joseph, Brownstein, John, Camara, Mamadi, Camara, Salif, Chai, Daniel, Chakraborty, Debapriyo, Chale, Hannah, Chaudhary, Ashok, Chea, Sokha, Chmura, Aleksei, Goossens, Benoit, Chow, Andrew, Churchill, Carolina, Commey, Abraham, Couacy-Hymann, Emmanuel, Coulibaly, Julien Kalpy, Cranfield, Michael, Damanik, Wirda, Damdinjav, Batchullum, Danial, Norhidayah, Dasak, Peter, David, Runie, Dawson, Patrick, Dembele, Arjouma, Deme, Awa, Desmond, James, Dewantari, Arghianditya Kresno, Dhanota, Jaseet, Dhole, Tapan, Diep, Nguyen Thi, Dionkounda, Artistide, Diop, Gaye Laye, Dodd, Kimberly, Dogby, Otilia, Dorjnyam, Tumendemberel, Dosso, Mireielle, Doumbouya, Kalil, Doumbouya, Mohamed Idriss, Doyle, Megan, Dramou, Simone, Drazenovich, Tracy, Duc Ahn, Dang, Duc Luu, Bach, Duendkae, Prateep, Duoc, Vu Trong, Duong, Tran Nhu, Duong, Veasna, Dursman, Huda, Dussart, Phillipe, Ee, Tan Jun, Ekiri, Abel, El Rifay, Amira S., El Shesheny, Rabel, El Taween, Ahmed N., Emmanuel, Zena Babu, Epstein, Jonathan H., Evans, Tierra Smiley, Fahmawi, Alaa, Fahn, Simeon, Feferholtz, Yasha, Ferdous, Jinnat, Fine, Amanda, Flora, Meerjady, Fransisco, Leilani, Fui Fui, Lem, Gabourie, Taylor, Gani, Millawati, Garbo, Michael, Gardner, Nicole, Gbamele, Marie, Ge, Xingyi, Gee, Lee Heng, Genovese, Brooke, Gibson, Alexandra, Gilardi, Kirsten, Gilbert, Martin, Gillis, Amethyst, Ginsos, Andrew, Godji Gnabro, Privat, Goldstein, Tracey, Gomaa, Moktar, Gomis, Jules, Gonzalez, Kevin, Grange, Zoe, Greig, Denise, Grodus, Michael, Gueu, Kpon Kakeuma Romeo, Gutierrez, Leticia, Haba, Dan Marcelin, Hamid, Suraya, Harris, Daniel K., Hashim, Abdul Kadir Abu, Hassan, Moushumi, Hassan, Quazar Nizamuddin, He, Qun, Hemachudha, Thiravat, Henry, Helen, Herbert, Ronald, Hijazeen, Zaidoun, Hilarion, Moukala Ndolo, Hill, Rebecca, Hoa, Nguyen Thi, Horwood, Paul, Hossain, Md. Enayet, Hossain, Saddam, Htun, Moh Moh, Hu, Ben, Hughes, Tom, Hul, Vibol, Van, Vo, Hussein, Fatima, Indola, Ghislain Dzeret, Iskandriati, Diah, Islam, Md. Tarikul, Islam, Shariful, Isnaim Ismail, Mohd, Ismail, Zuhair Bani, Iyanya, Jacques, Jaimin, Joel Judson, Jambai, Amara, Japning, Jeffrine Rovie Ryan, Japrin, Alexter, Jean Louis, Frantz, Joe, Titus, Johnson, Erica, Joly, Damien, Joshi, Jyotsna, Kalengkongan, Jusuf, Kalivogui, Douokoro, Kamara-Chieyoe, Nenneh, Kamau, Joseph, Kambale Syaluha, Eddy, Kandeil, Ahmed, Kane, Yogouba, Karesh, William, Kargo, Kandeh, Kasenda, Novie, Kayali, Ghazi, Kayed, Ahmed S., Kazwala, Rudovick, Ke, Changwen, Keates, Lucy, Kebede, Nigatu, Khamphaphongphane, Bouaphanh, Kheong, Chong Chee, Kilonzo, Christopher, Koffa, Ma-Sue, Kollie, Amos G., Kondiano, Marcel Sidik, Koropo, Michel, Kouamé Kouakou, Valere, Kouassi Koffi, Eugene, Kourouma, Mariam, Koutate, Abdoulaye Ousmane, Kowel, Citra Liv, Krou, Hermann Assemien, Kumakamba, Charles, Kutkat, Omnia, Lamah, François, Lan, Nguyen Thi, Lane, Jennifer, Lange, Christian, Larmouth, Emmanuel, Le Doux, Joseph Diffo, Leasure, Elizabeth, Leasure, Katherine, LeBreton, Mat, Lee, Jimmy, Lee, Helen, Lee, Mei Ho, Leno, Amara, Li, Hongying, Liang, Eliza, Liang, Neal, Lim, Dorothy, Lipkin, W. Ian, Liu, Jun, Lo, Modou Moustafa, Lojivis, Leonoris, Long, Nguyen Van, Lucas, Ashley, Lukusa, Jean Paul, Lungay, Victor, Lushima, Shongo, Lutwama, Julius, Ma, Wenjun, Machalaba, Catherine, Maganga, Grace, Magesa, Walter Simon, Mahmoud, Sara H., Makuwa, Maria, Makweta, Asha, Mamun, Abdullah Al, Manandhar, Prajwol, Maneeorn, Patarapol, Mann, Harjeet, Maomy, Bhele, Maptue, Victorine, Mathew, Alice, Mavoungou, Yanne Vanessa, Maw, Min Thein, Mazet, Jonna, Mbala, Placide, Mbuba, Emmanuel, Mbunwe, Eric, McIver, David, Mendelsohn, Emma, Miegakanda, Valchy Bel-Bebi, Minh, Phan Quang, Mkali, Happy, Moatasim, Yassmin, Mombouli, Jean Vivien, Monagin, Corina, Montecino-Latorre, Diego, Mossoun Mossoun, Arsene, Mostafa, Ahmed, Mouiche, Moctar, Mpassi, Romain Bagamboula, Msigwa, Alphonce, Mudakikwa, Antoine, Mugok, Laura Benedict, Mulembakani, Prime, Murray, Suzan, Musa, Fakhrul Hatta, Musabimana, Pacifique, Mutura, Samson, Mwamlima, Tunu, Mwanzanilla, Mwokozi, Myaing, Tin Tin, Myat, Theingi Win, Myo Chit, Aung, N’faly, Magassouba, N’Guettia, Manzan Jean, N’télo, Anatole, Nakimera, Sylivia, Nam, Vu Sinh, Napit, Rajindra, Nathan, Senthilvel K. S. S., Navarrete-Macias, Isamara, Ndebe, Kortu M., Ndiaye, Amadou, Ndiaye, Daouda, Negash, Yohannes, Nga, Nguyen Thi Thanh, Ngay, Ipos, Ngoc, Pham Thi Bich, Niama, Fabien, Nina, Rock Aimé, Niyonzima, Schadrack, Nkom, Felix, Nkoua, Cynthia, Noordin, Noorliza, Noviana, Rachmitasari, Nwobegahay, Julius, Nziza, Julius, O’Rourke, Daniel, O’Rourke, Tammie, Obodai, Evangeline, Okello Okwir, Ricky, Olival, Kevin, Olson, Sarah, Olva, Onkirotin Dionne, Ontiveros, Victoria, Opook, Fernandes, Panchadcharam, Chandrawathani, Pandit, Pranav, Parra, Henri-Joseph, Phuc, Tran Minh, Phuong, Nguyen Thanh, Poultolnor, Jackson Y., Pradhan, Saman, Preston, Eunah Cho, Pruvot, Mathieu, Purevtseren, Dulam, Puri, Dhiraj, Quang, Le Tin Vinh, Rachmitasari, Novie, Rahman, Kaisar, Rahman, Mizanur, Rahman, Mohammed Ziaur, Rahman, Mustafizur, Ramirez, Diana, Randhawa, Nistara, Raut, Samita, Rosario, Joseph, Ross, Albert, Ross, Noam, Rostal, Melinda, Roualdes, Pamela, Rubin, Eddy, Rumi, Aftab Uddin, Rundi, Christina, Sackie, Melkor, Sajali, Zikankuba, Samuels, Sandra G, Sango, Mathias, Saptu, Ammar Rafidah, Saraka, Daniel N’guessan, Sartee, Alvis A., Sayandouno, Sia Alida, Seck, Mame Cheikh, Sedor, Victoria, Sharma, Ajay Narayan, Sharminie, Velsri, Shehata, Mahmoud M., Sheikh, Gafur, Shi, Zhengli, Shiilegdamba, Enkhtuvshin, Shrestha, Bishwo, Shrestha, Rima, Sidibey, Mohammed, Silithammavong, Soubanh, Simon, Daniel, Sion, Emilly, Sipangkui, Symphorosa, Sitam, Frankie Thomas, Smith, Brett, Smith, Bridgette, Smith, Woutrina, Sodnom, Batsikhan, Ssebide, Benard, Suleiman, Maria, Sullivan, Ava, Sungif, Nur Amirah, Suu-Ire, Richard, Sy, Mouhamed, Takuo, Jean Michel, Talafha, Hani, Tamoufe, Ubald, Tetteh, Emmanuel, Than Toe, Aung, Thanda, Lanash, Thanh Long, Ngo, Thein, Wai Zin, Theppangna, Watthana, Thinh, Nguyen Duc, Thuy, Hoang Bich, Thuy, Nguyen Thu, Togami, Eri, Tolno, Moise Bendoua, Tolovou, Kevin, Topani, Rahmat, Tremeau-Bravard, Alexandre, Trupin, Ian, Tumushime, Jean Claude, Tun, Kyaw Yan Naing, Turay, Joseph, Uddin, Helal, Uhart, Marcela, Ureda, Nicole, Valitutto, Marc, Verasahib, Khebir, Vodzak, Megan, Wacharapluesadee, Supaporn, Wahad, Mohammad Yuery Wazlan Abdul, Watson, Brooke, Wells, Heather, White, Allison, Willoughby, Anna, Wiyatno, Ageng, Wolking, David, Yang, Xinglou, Yao, Lim Ming, Yombouno, Sayon, Young, Cristin, Zambrana-Torrelio, Carlos, Zeid, Zahidah Izzati, Zghoul, Ghadeer, Zhang, Libiao, Zhang, Yunzhi, Zhu, Guangjian, Zimmerman, Dawn, Zoumarou, Daba, Aguirre, Alonso, Aguirre, Luis, Akongo, Mark-Joel, Alandia Robles, Erika, Ambu, Laurentius, Ayala Aguilar, Glenda, Barcena, Luis, Barradas, Rosario, Basir, Misliah Mohamad, Bogich, Tiffany, Bounga, Gerard, Buchy, Philippe, Bunn, David, Byaruba, Denis, Cameron, Ken, Carroll, Dennis, Cavero, Nancy, Cespedes, Manuel, Che, Xiaoyu, Chiu, Charles, Chor, Kimashalen, Clements, Andrew, Dary Acevedo, Luz, de Almeida Campos, Angelica, De La Puente, Micaela, de Lamballerie, Xavier, de Paula, Catia, Delwart, Eric, Diffo Le Doux, Joseph, Doyle-Capitman, Catherine, Durigon, Edison, Fair, Joseph, Ferrer-Paris, José R., Formenty, Pierre, Galarza, Isabel, Garcia, Joel, Grard, Gilda, Greatorex, Zoe, Harris, Laurie, Hitchens, Peta, Ho, Mei, Hosseini, Parviez, In, Samath, Iñíguez, Volga, Jain, Komal, Jamaluddin, Abd. Aziz, Johnson, Christine, Jones, Kate, Joyner, Priscilla, Kaba, Serge, Kambale, Eddy, Kataregga, Abdulhameed, Kelly, Terra, Khammavong, Kongsy, Kilpatrick, A. Marm, Laimun, Samsir, Lee, Mei-Ho, LeRoy, Eric, Levinson, Jordan, Levy, Marc, Limachi, Rolando, Loh, Elizabeth, Lowenstine, Linda J., Luis Mollericona, José, Maganga, Ruth, Malakalinga, Joseph, Manhas, Melissa, Marra, Pete, Mbabazi, Rachael, Medellín, Rodrigo, Mendoza, Patricia, Miller, Sireeda, Miranda, Flavia, Mitchell, Megan, Mohamed, Ramlan, Mollard, Debbie, Morse, Stephen, Mouellet, Wivine, Moya, Isabel, Murillo, Yovanna, Murray, Kris, Muyembe Tamfum, Jean-Jacques, Nassar, Fernando, Nathan, Sen, Nsengimana, Olivier, Ogg Keatts, Lucy, Ojeda-Flore, Rafael, Okwir Okello, Ricky, Ondzie, Alain, Paweska, Janusz, Pereira, Alisa, Pereira, Victoria, Perez, Alberto, Perez, Jocelyn, Phon, Simorn, Reed, Patricia, Rejmanek, Dan, Rico, Oscar, Rivera, Rosario, Romero, Monica, Roy, Celina, Saepuloh, Uus, Schneider, Brad, Schwind, Jessica, Singhalath, Sinpakhome, Smith, Kristine, Suárez, Fabiola, Suzan, Gerardo, Thanh Nga, Nguyen Thi, Thomas, Kate, Ticona, Herminio, VanWormer, Elizabeth, Villar, Sandra, Weisman, Wendy, Westfall, Michael, Whittier, Chris, Wicker, Leanne, Wolfe, Nathan, Yang, Angela, Zariquiey, Carlos, Zhang, Shu-Yi, Zorine Nkouants, Baudelaire, Zainuddin, Zainal, Chrisman, Cara, Pabst, August, Shek, Amalhin, and Trostle, Murray

Subjects
0301 basic medicine, Behavioral risk, medicine.medical_specialty, Behavioural sciences, Disease, Community integration, Basic Behavioral and Social Science, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, 2.3 Psychological, Behavioral and Social Science, Agency (sociology), medicine, 2.2 Factors relating to the physical environment, GE1-350, Aetiology, One health, Social science research, business.industry, Prevention, Research, Public health, PREDICT Consortium, Public relations, Focus group, Environmental sciences, Good Health and Well Being, 030104 developmental biology, One Health, Multi-disciplinary surveillance, social and economic factors, Public aspects of medicine, RA1-1270, Infection, Psychology, International development, business, 030217 neurology & neurosurgery
Abstract

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security. Supplementary Information The online version contains supplementary material available at 10.1186/s42522-021-00036-9.

Published
2021

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