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42 results on '"Bogich, Tiffany"'

1. Multiple models for outbreak decision support in the face of uncertainty.

Author

Shea, Katriona, Borchering, Rebecca K, Probert, William JM, Howerton, Emily, Bogich, Tiffany L, Li, Shou-Li, van Panhuis, Willem G, Viboud, Cecile, Aguás, Ricardo, Belov, Artur A, Bhargava, Sanjana H, Cavany, Sean M, Chang, Joshua C, Chen, Cynthia, Chen, Jinghui, Chen, Shi, Chen, YangQuan, Childs, Lauren M, Chow, Carson C, Crooker, Isabel, Del Valle, Sara Y, España, Guido, Fairchild, Geoffrey, Gerkin, Richard C, Germann, Timothy C, Gu, Quanquan, Guan, Xiangyang, Guo, Lihong, Hart, Gregory R, Hladish, Thomas J, Hupert, Nathaniel, Janies, Daniel, Kerr, Cliff C, Klein, Daniel J, Klein, Eili Y, Lin, Gary, Manore, Carrie, Meyers, Lauren Ancel, Mittler, John E, Mu, Kunpeng, Núñez, Rafael C, Oidtman, Rachel J, Pasco, Remy, Pastore Y Piontti, Ana, Paul, Rajib, Pearson, Carl AB, Perdomo, Dianela R, Perkins, T Alex, Pierce, Kelly, Pillai, Alexander N, Rael, Rosalyn Cherie, Rosenfeld, Katherine, Ross, Chrysm Watson, Spencer, Julie A, Stoltzfus, Arlin B, Toh, Kok Ben, Vattikuti, Shashaank, Vespignani, Alessandro, Wang, Lingxiao, White, Lisa J, Xu, Pan, Yang, Yupeng, Yogurtcu, Osman N, Zhang, Weitong, Zhao, Yanting, Zou, Difan, Ferrari, Matthew J, Pannell, David, Tildesley, Michael J, Seifarth, Jack, Johnson, Elyse, Biggerstaff, Matthew, Johansson, Michael A, Slayton, Rachel B, Levander, John D, Stazer, Jeff, Kerr, Jessica, and Runge, Michael C

Subjects
Humans, Uncertainty, Public Health, Disease Outbreaks, Pandemics, COVID-19, cognitive biases, decision theory, multi-model aggregation, Prevention, Brain Disorders, Good Health and Well Being
Abstract

Policymakers must make management decisions despite incomplete knowledge and conflicting model projections. Little guidance exists for the rapid, representative, and unbiased collection of policy-relevant scientific input from independent modeling teams. Integrating approaches from decision analysis, expert judgment, and model aggregation, we convened multiple modeling teams to evaluate COVID-19 reopening strategies for a mid-sized United States county early in the pandemic. Projections from seventeen distinct models were inconsistent in magnitude but highly consistent in ranking interventions. The 6-mo-ahead aggregate projections were well in line with observed outbreaks in mid-sized US counties. The aggregate results showed that up to half the population could be infected with full workplace reopening, while workplace restrictions reduced median cumulative infections by 82%. Rankings of interventions were consistent across public health objectives, but there was a strong trade-off between public health outcomes and duration of workplace closures, and no win-win intermediate reopening strategies were identified. Between-model variation was high; the aggregate results thus provide valuable risk quantification for decision making. This approach can be applied to the evaluation of management interventions in any setting where models are used to inform decision making. This case study demonstrated the utility of our approach and was one of several multimodel efforts that laid the groundwork for the COVID-19 Scenario Modeling Hub, which has provided multiple rounds of real-time scenario projections for situational awareness and decision making to the Centers for Disease Control and Prevention since December 2020.

Published
2023

2. The US COVID-19 and Influenza Scenario Modeling Hubs: Delivering long-term projections to guide policy

Author

Loo, Sara L., Howerton, Emily, Contamin, Lucie, Smith, Claire P., Borchering, Rebecca K., Mullany, Luke C., Bents, Samantha, Carcelen, Erica, Jung, Sung-mok, Bogich, Tiffany, van Panhuis, Willem G., Kerr, Jessica, Espino, Jessi, Yan, Katie, Hochheiser, Harry, Runge, Michael C., Shea, Katriona, Lessler, Justin, Viboud, Cécile, and Truelove, Shaun

Published
2024
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3. Targeting Transmission Pathways for Emerging Zoonotic Disease Surveillance and Control

Author

Loh, Elizabeth H, Zambrana-Torrelio, Carlos, Olival, Kevin J, Bogich, Tiffany L, Johnson, Christine K, Mazet, Jonna AK, Karesh, William, and Daszak, Peter

Subjects
2.4 Surveillance and distribution, Aetiology, Infection, Good Health and Well Being, Agriculture, Animals, Communicable Diseases, Emerging, Demography, Disease Reservoirs, Environment, Epidemiological Monitoring, Humans, Public Health, Travel, Zoonoses, Surveillance, Transmission routes, Pathway, Direct contact, Vector-borne, Virus, Zoonosis, Public Health and Health Services, Tropical Medicine
Abstract

We used literature searches and a database of all reported emerging infectious diseases (EIDs) to analyze the most important transmission pathways (e.g., vector-borne, aerosol droplet transmitted) for emerging zoonoses. Our results suggest that at the broad scale, the likelihood of transmission occurring through any one pathway is approximately equal. However, the major transmission pathways for zoonoses differ widely according to the specific underlying drivers of EID events (e.g., land-use change, agricultural intensification). These results can be used to develop better targeting of surveillance for, and more effective control of newly emerged zoonoses in regions under different underlying pressures that drive disease emergence.

Published
2015

4. SSM: Inference for time series analysis with State Space Models

Author

Dureau, Joseph, Ballesteros, Sébastien, and Bogich, Tiffany

Subjects
Statistics - Computation
Abstract

The main motivation behind the open source library SSM is to reduce the technical friction that prevents modellers from sharing their work, quickly iterating in crisis situations, and making their work directly usable by public authorities to serve decision-making.

Published
2013

5. The path of least resistance: aggressive or moderate treatment?

Author

Kouyos, Roger D, Metcalf, C Jessica E, Birger, Ruthie, Klein, Eili Y, Wiesch, Pia Abel zur, Ankomah, Peter, Arinaminpathy, Nimalan, Bogich, Tiffany L, Bonhoeffer, Sebastian, Brower, Charles, Chi-Johnston, Geoffrey, Cohen, Ted, Day, Troy, Greenhouse, Bryan, Huijben, Silvie, Metlay, Joshua, Mideo, Nicole, Pollitt, Laura C, Read, Andrew F, Smith, David L, Standley, Claire, Wale, Nina, and Grenfell, Bryan

Subjects
Emerging Infectious Diseases, Antimicrobial Resistance, 6.1 Pharmaceuticals, Evaluation of treatments and therapeutic interventions, Infection, Good Health and Well Being, Anti-Infective Agents, Biological Evolution, Drug Resistance, Microbial, Humans, Infections, Microbiota, drug resistance, evolution, treatment strategies, Biological Sciences, Agricultural and Veterinary Sciences, Medical and Health Sciences
Abstract

The evolution of resistance to antimicrobial chemotherapy is a major and growing cause of human mortality and morbidity. Comparatively little attention has been paid to how different patient treatment strategies shape the evolution of resistance. In particular, it is not clear whether treating individual patients aggressively with high drug dosages and long treatment durations, or moderately with low dosages and short durations can better prevent the evolution and spread of drug resistance. Here, we summarize the very limited available empirical evidence across different pathogens and provide a conceptual framework describing the information required to effectively manage drug pressure to minimize resistance evolution.

Published
2014

6. A Strategy To Estimate Unknown Viral Diversity in Mammals

Author

Anthony, Simon J, Epstein, Jonathan H, Murray, Kris A, Navarrete-Macias, Isamara, Zambrana-Torrelio, Carlos M, Solovyov, Alexander, Ojeda-Flores, Rafael, Arrigo, Nicole C, Islam, Ariful, Khan, Shahneaz Ali, Hosseini, Parviez, Bogich, Tiffany L, Olival, Kevin J, Sanchez-Leon, Maria D, Karesh, William B, Goldstein, Tracey, Luby, Stephen P, Morse, Stephen S, Mazet, Jonna AK, Daszak, Peter, and Lipkin, W Ian

Subjects
Biological Sciences, Ecology, Infection, Life Below Water, Animals, Animals, Wild, Biodiversity, Chiroptera, Molecular Sequence Data, Phylogeny, Polymerase Chain Reaction, Viruses, Zoonoses, Microbiology, Biochemistry and cell biology, Medical microbiology
Abstract

UnlabelledThe majority of emerging zoonoses originate in wildlife, and many are caused by viruses. However, there are no rigorous estimates of total viral diversity (here termed "virodiversity") for any wildlife species, despite the utility of this to future surveillance and control of emerging zoonoses. In this case study, we repeatedly sampled a mammalian wildlife host known to harbor emerging zoonotic pathogens (the Indian Flying Fox, Pteropus giganteus) and used PCR with degenerate viral family-level primers to discover and analyze the occurrence patterns of 55 viruses from nine viral families. We then adapted statistical techniques used to estimate biodiversity in vertebrates and plants and estimated the total viral richness of these nine families in P. giganteus to be 58 viruses. Our analyses demonstrate proof-of-concept of a strategy for estimating viral richness and provide the first statistically supported estimate of the number of undiscovered viruses in a mammalian host. We used a simple extrapolation to estimate that there are a minimum of 320,000 mammalian viruses awaiting discovery within these nine families, assuming all species harbor a similar number of viruses, with minimal turnover between host species. We estimate the cost of discovering these viruses to be ~$6.3 billion (or ~$1.4 billion for 85% of the total diversity), which if annualized over a 10-year study time frame would represent a small fraction of the cost of many pandemic zoonoses.ImportanceRecent years have seen a dramatic increase in viral discovery efforts. However, most lack rigorous systematic design, which limits our ability to understand viral diversity and its ecological drivers and reduces their value to public health intervention. Here, we present a new framework for the discovery of novel viruses in wildlife and use it to make the first-ever estimate of the number of viruses that exist in a mammalian host. As pathogens continue to emerge from wildlife, this estimate allows us to put preliminary bounds around the potential size of the total zoonotic pool and facilitates a better understanding of where best to allocate resources for the subsequent discovery of global viral diversity.

Published
2013

7. Targeting Surveillance for Zoonotic Virus Discovery - Volume 19, Number 5—May 2013 - Emerging Infectious Diseases journal - CDC

Author

Levinson, Jordan, Bogich, Tiffany L, Olival, Kevin J, Epstein, Jonathan H, Johnson, Christine K, Karesh, William, and Daszak, Peter

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Prevention, Rare Diseases, Infectious Diseases, Vaccine Related, Emerging Infectious Diseases, Biodefense, Infection, Good Health and Well Being, Animals, Chiroptera, Communicable Diseases, Emerging, Disease Reservoirs, Epidemiological Monitoring, Global Health, Host-Pathogen Interactions, Humans, Models, Statistical, Rodentia, Virus Diseases, Viruses, Zoonoses, ecohealth, mammals, pathogen, reservoir host, surveillance, virus discovery, viruses, wildlife, zoonoses, Medical Microbiology, Public Health and Health Services, Microbiology, Clinical sciences, Epidemiology, Health services and systems
Abstract

We analyzed a database of mammal-virus associations to ask whether surveillance targeting diseased animals is the best strategy to identify potentially zoonotic pathogens. Although a mixed healthy and diseased animal surveillance strategy is generally best, surveillance of apparently healthy animals would likely maximize zoonotic virus discovery potential for bats and rodents.

Published
2013

9. Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology

Author

Howerton, Emily, primary, Runge, Michael C., additional, Bogich, Tiffany L., additional, Borchering, Rebecca K., additional, Inamine, Hidetoshi, additional, Lessler, Justin, additional, Mullany, Luke C., additional, Probert, William J. M., additional, Smith, Claire P., additional, Truelove, Shaun, additional, Viboud, Cécile, additional, and Shea, Katriona, additional

Published
2023
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10. Electronic Supplementary Material from Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology

Author

Howerton, Emily, Runge, Michael C., Bogich, Tiffany L., Borchering, Rebecca K., Inamine, Hidetoshi, Lessler, Justin, Mullany, Luke C., Probert, William J. M., Smith, Claire P., Truelove, Shaun, Viboud, Cécile, and Shea, Katriona

Abstract

Additional information on theory and case studies discussed in Context-dependent representation of within- and between-model uncertainty: aggregating probabilistic predictions in infectious disease epidemiology

Published
2023
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13. The path of least resistance: aggressive or moderate treatment?

Author

Kouyos, Roger D., Metcalf, C. Jessica E., Birger, Ruthie, Klein, Eili Y., zur Wiesch, Pia Abel, Ankomah, Peter, Arinaminpathy, Nimalan, Bogich, Tiffany L., Bonhoeffer, Sebastian, Brower, Charles, Chi-Johnston, Geoffrey, Cohen, Ted, Day, Troy, Greenhouse, Bryan, Huijben, Silvie, Metlay, Joshua, Mideo, Nicole, Pollitt, Laura C., Read, Andrew F., Smith, David L., Standley, Claire, Wale, Nina, and Grenfell, Bryan

Published
2014

19. Synergistic interventions to control COVID-19: Mass testing and isolation mitigates reliance on distancing

Author

Howerton, Emily, primary, Ferrari, Matthew J., additional, Bjørnstad, Ottar N., additional, Bogich, Tiffany L., additional, Borchering, Rebecca K., additional, Jewell, Chris P., additional, Nichols, James D., additional, Probert, William J. M., additional, Runge, Michael C., additional, Tildesley, Michael J., additional, Viboud, Cécile, additional, and Shea, Katriona, additional

Published
2021
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20. 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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22. Strategic testing approaches for targeted disease monitoring can be used to inform pandemic decision-making

Author

Nichols, James D., primary, Bogich, Tiffany L., additional, Howerton, Emily, additional, Bjørnstad, Ottar N., additional, Borchering, Rebecca K., additional, Ferrari, Matthew, additional, Haran, Murali, additional, Jewell, Christopher, additional, Pepin, Kim M., additional, Probert, William J. M., additional, Pulliam, Juliet R. C., additional, Runge, Michael C., additional, Tildesley, Michael, additional, Viboud, Cécile, additional, and Shea, Katriona, additional

Published
2021
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23. Erratum: Host and viral traits predict zoonotic spillover from mammals

Author

Olival, Kevin J., Hosseini, Parviez R., Zambrana-Torrelio, Carlos, Ross, Noam, Bogich, Tiffany L., and Daszak, Peter

Subjects
Environmental issues, Science and technology, Zoology and wildlife conservation
Abstract

Author(s): Kevin J. Olival; Parviez R. Hosseini; Carlos Zambrana-Torrelio; Noam Ross; Tiffany L. Bogich; Peter Daszak Nature 546, 646650 (2017); doi:10.1038/nature22975 In this Letter, owing to an error during the [...]

Published
2017
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26. COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support

Author

Shea, Katriona, primary, Borchering, Rebecca K., additional, Probert, William J.M., additional, Howerton, Emily, additional, Bogich, Tiffany L., additional, Li, Shouli, additional, van Panhuis, Willem G., additional, Viboud, Cecile, additional, Aguás, Ricardo, additional, Belov, Artur, additional, Bhargava, Sanjana H., additional, Cavany, Sean, additional, Chang, Joshua C., additional, Chen, Cynthia, additional, Chen, Jinghui, additional, Chen, Shi, additional, Chen, YangQuan, additional, Childs, Lauren M., additional, Chow, Carson C., additional, Crooker, Isabel, additional, Del Valle, Sara Y., additional, España, Guido, additional, Fairchild, Geoffrey, additional, Gerkin, Richard C., additional, Germann, Timothy C., additional, Gu, Quanquan, additional, Guan, Xiangyang, additional, Guo, Lihong, additional, Hart, Gregory R., additional, Hladish, Thomas J., additional, Hupert, Nathaniel, additional, Janies, Daniel, additional, Kerr, Cliff C., additional, Klein, Daniel J., additional, Klein, Eili, additional, Lin, Gary, additional, Manore, Carrie, additional, Meyers, Lauren Ancel, additional, Mittler, John, additional, Mu, Kunpeng, additional, Núñez, Rafael C., additional, Oidtman, Rachel, additional, Pasco, Remy, additional, Piontti, Ana Pastore y, additional, Paul, Rajib, additional, Pearson, Carl A. B., additional, Perdomo, Dianela R., additional, Perkins, T Alex, additional, Pierce, Kelly, additional, Pillai, Alexander N., additional, Rael, Rosalyn Cherie, additional, Rosenfeld, Katherine, additional, Ross, Chrysm Watson, additional, Spencer, Julie A., additional, Stoltzfus, Arlin B., additional, Toh, Kok Ben, additional, Vattikuti, Shashaank, additional, Vespignani, Alessandro, additional, Wang, Lingxiao, additional, White, Lisa, additional, Xu, Pan, additional, Yang, Yupeng, additional, Yogurtcu, Osman N., additional, Zhang, Weitong, additional, Zhao, Yanting, additional, Zou, Difan, additional, Ferrari, Matthew, additional, Pannell, David, additional, Tildesley, Michael, additional, Seifarth, Jack, additional, Johnson, Elyse, additional, Biggerstaff, Matthew, additional, Johansson, Michael, additional, Slayton, Rachel B., additional, Levander, John, additional, Stazer, Jeff, additional, Salerno, Jessica, additional, and Runge, Michael C., additional

Published
2020
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29. Preventing pandemics via international development: a systems approach

Author

Bogich, Tiffany L., Chunara, Rumi, Scales, David, Chan, Emily, Pinheiro, Laura C., Chmura, Aleksei A., Carroll, Dennis, Daszak, Peter, and Brownstein, John S.

Subjects
Epidemics -- Prevention -- Political aspects -- United States, Medical policy -- Management, Disease transmission -- Control -- Political aspects, Company business management, Biological sciences
Abstract

Outbreaks, Driving Factors, and Development Outbreaks of emerging infectious diseases place significant burden on public health and global economies [1]. The process leading to spillover, localized emergence, and finally pandemic [...]

Published
2012
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30. Solution scanning as a key policy tool

Author

Sutherland, William J., Gardner, Toby, Bogich, Tiffany L., Bradbury, Richard B., Clothier, Brent, Jonsson, Mattias, Kapos, Val, Lane, Stuart N., Möller, Iris, Schroeder, Martin, Spalding, Mark, Spencer, Tom, White, Piran C.L, and Dicks, Lynn V.

Subjects
Ecology
Abstract

The major task of policy makers and practitioners when confronted with a resource management problem is to decide on the potential solution(s) to adopt from a range of available options. However, this process is unlikely to be successful and cost effective without access to an independently verified and comprehensive available list of options. There is currently burgeoning interest in ecosystem services and quantitative assessments of their importance and value. Recognition of the value of ecosystem services to human well-being represents an increasingly important argument for protecting and restoring the natural environment, alongside the moral and ethical justifications for conservation. As well as understanding the benefits of ecosystem services, it is also important to synthesize the practical interventions that are capable of maintaining and/or enhancing these services. Apart from pest regulation, pollination, and global climate regulation, this type of exercise has attracted relatively little attention. Through a systematic consultation exercise, we identify a candidate list of 296 possible interventions across the main regulating services of air quality regulation, climate regulation, water flow regulation, erosion regulation, water purification and waste treatment, disease regulation, pest regulation, pollination and natural hazard regulation. The range of interventions differs greatly between habitats and services depending upon the ease of manipulation and the level of research intensity. Some interventions have the potential to deliver benefits across a range of regulating services, especially those that reduce soil loss and maintain forest cover. Synthesis and applications: Solution scanning is important for questioning existing knowledge and identifying the range of options available to researchers and practitioners, as well as serving as the necessary basis for assessing cost effectiveness and guiding implementation strategies. We recommend that it become a routine part of decision making in all environmental policy areas.

Published
2014
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35. Targeting surveillance for zoonotic virus discovery.

Author

Levinson, Jordan, Levinson, Jordan, Bogich, Tiffany L, Olival, Kevin J, Epstein, Jonathan H, Johnson, Christine K, Karesh, William, Daszak, Peter, Levinson, Jordan, Levinson, Jordan, Bogich, Tiffany L, Olival, Kevin J, Epstein, Jonathan H, Johnson, Christine K, Karesh, William, and Daszak, Peter

Abstract

We analyzed a database of mammal-virus associations to ask whether surveillance targeting diseased animals is the best strategy to identify potentially zoonotic pathogens. Although a mixed healthy and diseased animal surveillance strategy is generally best, surveillance of apparently healthy animals would likely maximize zoonotic virus discovery potential for bats and rodents.

Published
2013

36. Adaptive Management of Bull Trout Populations in the Lemhi Basin

Author

Tyre, Andrew J., Peterson, James T., Converse, Sarah J., Bogich, Tiffany, Miller, Damien, Burg, Max Post van der, Thomas, Carmen, Thompson, Ralph, Wood, Jeri, Brewer, Donna C., Runge, Michael C., Tyre, Andrew J., Peterson, James T., Converse, Sarah J., Bogich, Tiffany, Miller, Damien, Burg, Max Post van der, Thomas, Carmen, Thompson, Ralph, Wood, Jeri, Brewer, Donna C., and Runge, Michael C.

Abstract

The bull trout Salvelinus confluentus, a stream-living salmonid distributed in drainages of the northwestern United States, is listed as threatened under the Endangered Species Act because of rangewide declines. One proposed recovery action is the reconnection of tributaries in the Lemhi Basin. Past water use policies in this core area disconnected headwater spawning sites from downstream habitat and have led to the loss of migratory life history forms. We developed an adaptive management framework to analyze which types of streams should be prioritized for reconnection under a proposed Habitat Conservation Plan. We developed a Stochastic Dynamic Program that identified optimal policies over time under four different assumptions about the nature of the migratory behavior and the effects of brook trout Salvelinus fontinalis on subpopulations of bull trout. In general, given the current state of the system and the uncertainties about the dynamics, the optimal policy would be to connect streams that are currently occupied by bull trout. We also estimated the value of information as the difference between absolute certainty about which of our four assumptions were correct, and a model averaged optimization assuming no knowledge. Overall there is little to be gained by learning about the dynamics of the system in its current state, although in other parts of the state space reducing uncertainties about the system would be very valuable. We also conducted a sensitivity analysis; the optimal decision at the current state does not change even when parameter values are changed up to 75% of the baseline values. Overall, the exercise demonstrates that it is possible to apply adaptive management principles to threatened and endangered species, but logistical and data availability constraints make detailed analyses difficult.

Published
2011

38. Using network theory to identify the causes of disease outbreaks of unknown origin

Author

Bogich, Tiffany L., primary, Funk, Sebastian, additional, Malcolm, Trent R., additional, Chhun, Nok, additional, Epstein, Jonathan H., additional, Chmura, Aleksei A., additional, Kilpatrick, A. Marm, additional, Brownstein, John S., additional, Hutchison, O. Clyde, additional, Doyle-Capitman, Catherine, additional, Deaville, Robert, additional, Morse, Stephen S., additional, Cunningham, Andrew A., additional, and Daszak, Peter, additional

Published
2013
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41. Adaptive Management of Bull Trout Populations in the Lemhi Basin

Author

Tyre, Andrew J., primary, Peterson, James T., additional, Converse, Sarah J., additional, Bogich, Tiffany, additional, Miller, Damien, additional, van der Burg, Max Post, additional, Thomas, Carmen, additional, Thompson, Ralph, additional, Wood, Jeri, additional, Brewer, Donna C., additional, and Runge, Michael C., additional

Published
2011
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42. COVID-19 reopening strategies at the county level in the face of uncertainty: Multiple Models for Outbreak Decision Support.

Author

Shea K, Borchering RK, Probert WJM, Howerton E, Bogich TL, Li S, van Panhuis WG, Viboud C, Aguás R, Belov A, Bhargava SH, Cavany S, Chang JC, Chen C, Chen J, Chen S, Chen Y, Childs LM, Chow CC, Crooker I, Valle SYD, España G, Fairchild G, Gerkin RC, Germann TC, Gu Q, Guan X, Guo L, Hart GR, Hladish TJ, Hupert N, Janies D, Kerr CC, Klein DJ, Klein E, Lin G, Manore C, Meyers LA, Mittler J, Mu K, Núñez RC, Oidtman R, Pasco R, Piontti APY, Paul R, Pearson CAB, Perdomo DR, Perkins TA, Pierce K, Pillai AN, Rael RC, Rosenfeld K, Ross CW, Spencer JA, Stoltzfus AB, Toh KB, Vattikuti S, Vespignani A, Wang L, White L, Xu P, Yang Y, Yogurtcu ON, Zhang W, Zhao Y, Zou D, Ferrari M, Pannell D, Tildesley M, Seifarth J, Johnson E, Biggerstaff M, Johansson M, Slayton RB, Levander J, Stazer J, Salerno J, and Runge MC

Abstract

Policymakers make decisions about COVID-19 management in the face of considerable uncertainty. We convened multiple modeling teams to evaluate reopening strategies for a mid-sized county in the United States, in a novel process designed to fully express scientific uncertainty while reducing linguistic uncertainty and cognitive biases. For the scenarios considered, the consensus from 17 distinct models was that a second outbreak will occur within 6 months of reopening, unless schools and non-essential workplaces remain closed. Up to half the population could be infected with full workplace reopening; non-essential business closures reduced median cumulative infections by 82%. Intermediate reopening interventions identified no win-win situations; there was a trade-off between public health outcomes and duration of workplace closures. Aggregate results captured twice the uncertainty of individual models, providing a more complete expression of risk for decision-making purposes.

Published
2020
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