Current projects
We use dynamical models, statistical models, and data analysis to support decision-making around policies to manage infectious disease, focusing on malaria and COVID-19.
For malaria, we use agent-based models to understand how to achieve malaria control, elimination, and global eradication in resource-limited settings. Current projects include:
For COVID-19, we supported Illinois and Chicago departments of public health in making evidence-based policy for COVID-19 containment, focusing on quantifying disparities and improving surveillance. Our COVID-19 work was/is supported by grants from MIDAS, NUCATS, the Crown Seed Covid Fund's NU-TAU joint award program, and the Peterson Foundation. Our COVID-19 outputs and model are publicly available.
For malaria, we use agent-based models to understand how to achieve malaria control, elimination, and global eradication in resource-limited settings. Current projects include:
- in partnership with WHO under the High Burden to High Impact (HBHI) initiative, supporting national malaria strategic planning in Burkina Faso, Nigeria, and Guinea by providing impact estimates of subnationally-tailored intervention mix plans to national malaria control programs (NMCPs)
- as part of HBHI in Burkina, characterizing trends in routine case data adjusting for improved surveillance and estimating the impact of seasonal malaria chemoprevention (SMC)
- as part of HBHI in Burkina, understanding individual-level risk factors for clinical malaria in children under 5
- as part of HBHI in Guinea, identifying factors associated with insecticide-treated net ownership and use
- in partnership with WHO, a qualitative assessment of NMCP experiences with stratification and subnational tailoring under HBHI
- in partnership with WHO, predicting the impact of RTS,S under operationally feasible distribution
- in partnership with Malaria Consortium, predicting the impact of intermittent preventive treatment for infants (IPTi) in Nigeria and beyond
- in partnership with the INDIE study, exploring how targeting the asymptomatic reservoir with screening, testing, and treating programs could reduce burden or help achieve elimination
- in partnership with the University of Ghana, understanding how SMC has altered the infectious reservoir of malaria
- landscaping how to build a collaborative, successful, and sustainable capacity-acceleration program for data analysis and modeling to support decision-making in NMCPs
- Analysis of demographic and health surveys to understand the burden and determinants of malaria transmission in urban areas and to inform related field studies
- in partnership with the Nigerian Malaria Elimination Programme, the WHO and Gates Foundation, conducting epidemiological and entomological studies in urban Nigeria to better understand malaria risk, build models of malaria transmission in urban areas, and ultimately design urban microstratification schemes
- in partnership with WHO, understanding the distribution of insecticide-treated nets in urban areas in malaria-endemic countries
For COVID-19, we supported Illinois and Chicago departments of public health in making evidence-based policy for COVID-19 containment, focusing on quantifying disparities and improving surveillance. Our COVID-19 work was/is supported by grants from MIDAS, NUCATS, the Crown Seed Covid Fund's NU-TAU joint award program, and the Peterson Foundation. Our COVID-19 outputs and model are publicly available.
Publications: Malaria
High-burden settings
Preprint: Socioeconomic, demographic and environmental factors inform intervention prioritization in urban Nigeria.
Chiziba C., Diallo O., Bertozzi-Villa A., Weiss D., Mercer L., Gerardin J., Ozodiegwu I.D. medRxiv (2022).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Intervention mixes for control and elimination
Modeling impact and cost‐effectiveness of driving‐Y gene drives for malaria elimination in the Democratic Republic of the Congo.
Metchanun N., Borgemeister C., Amzati G., von Braun J., Nikolov M., Selvaraj P., Gerardin J. Evolutionary Applications. 15:132–148 (2022).
Vector genetics, insecticide resistance and gene drives: an agent-based modeling approach to evaluate malaria transmission and elimination.
Selvaraj P., Wenger E.A., Bridenbecker D., Windbichler N., Russell J.R., Gerardin J., Bever C.A., Nikolov M. PLoS Computational Biology. 16(8): e1008121 (2020).
Reducing malaria burden and accelerating elimination with long-lasting systemic insecticides: a modelling study of three potential use cases.
Selvaraj P.*, Suresh J.*, Wenger E.A., Bever C.A., and Gerardin J. Malaria Journal 18:307 (2019).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study.
Gerardin J., Bever C.A., Bridenbecker D., Hamainza B., Silumbe K., Miller J.M., Eisele T.P., Eckhoff P.A., and Wenger E.A. Malaria Journal 16:248 (2017).
Malaria elimination in the Lake Kariba region of Zambia: a spatial dynamical model.
Nikolov M., Bever C.A., Upfill-Brown A., Hamainza B., Miller J.M., Eckhoff P.A., Wenger E.A., and Gerardin J. PLoS Computational Biology 12(11):e1005192 (2016).
Drug-based strategies
Long-term effects of increased adoption of artemisinin combination therapies in Burkina Faso.
Zupko R., Nguyen T.D., Some A.F., Tran T.N., Gerardin J., Dudas P., Giang D.D., Wesolowski A., Ouedraogo J.B., Boni M.F. PLoS Global Public Health 2(2): e0000111 (2022).
Impact of mass drug administration campaigns depends on interaction with seasonal human movement.
Gerardin J., Bertozzi-Villa A., Eckhoff P.A., and Wenger E.A. International Health 10:1 (2018).
Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study.
Brady O.J., Slater H.C., Pemberton-Ross P., Wenger E., Maude R.J., Ghani A.C., Penny M.A., Gerardin J., White L.J., Chitnis N., Aguas R., Hay S.I., Smith D.L., Stuckey E.M., Okiro E.A., Smith T.A., and Okell L.C. Lancet Global Health 5(7):e680 (2017).
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study.
Gerardin J., Bever C.A., Bridenbecker D., Hamainza B., Silumbe K., Miller J.M., Eisele T.P., Eckhoff P.A., and Wenger E.A. Malaria Journal 16:248 (2017).
Malaria elimination in the Lake Kariba region of Zambia: a spatial dynamical model.
Nikolov M., Bever C.A., Upfill-Brown A., Hamainza B., Miller J.M., Eckhoff P.A., Wenger E.A., and Gerardin J. PLoS Computational Biology 12(11):e1005192 (2016).
Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission.
Gerardin J., Bever C.A., Hamainza B., Miller J.M., Eckhoff P.A., and Wenger E.A. PLoS Computational Biology 12(1):e1004707 (2016).
Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination.
Gerardin J., Eckhoff P.A., and Wenger E.A. BMC Infectious Diseases 15:144 (2015).
Infectious reservoir and infection detection
Investigating the impact of enhanced community case management and monthly screening and treatment on the transmissibility of malaria infections in Burkina Faso: study protocol for a cluster-randomised trial
Collins K.A., Ouedraogo A., Guelbeogo W.M., Awandu S.S., Stone W., Soulama I., Ouattara M., Nombre A., Diarra A., Bradley J., Selvaraj P., Gerardin J., Drakeley C., Bousema T., Tiono A.B. BMJ Open. 9:e030598 (2019).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission.
Gerardin J., Bever C.A., Hamainza B., Miller J.M., Eckhoff P.A., and Wenger E.A. PLoS Computational Biology 12(1):e1004707 (2016).
Dynamics of the human infectious reservoir for malaria determined by mosquito feeding assay an ultra-sensitive malaria diagnosis in Burkina Faso.
Ouédraogo A.L., Gonçalves B.P., Gnémé A., Wenger E.A., Guelbeogo M.W., Ouédraogo A., Gerardin J., Bever C.A., Lyons H., Pitroipa X., Verhave J.P., Eckhoff P.A., Drakeley C., Sauerwein R., Luty A.J.F., Kouyaté B., and Bousema T. Journal of Infectious Diseases 213(1):90-99 (2016).
Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness.
Gerardin J., Ouédraogo A.L., McCarthy K.A., Eckhoff P.A., and Wenger E.A. Malaria Journal 14:231 (2015).
Model calibration
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness.
Gerardin J., Ouédraogo A.L., McCarthy K.A., Eckhoff P.A., and Wenger E.A. Malaria Journal 14:231 (2015).
Model development
Implementation and applications of the EMOD individual-based disease modeling platform: software design and development processes to enable multi-scale modeling.
Bershteyn A., Gerardin J., Bridenbecker D., Lorton C., et al. on behalf of the Institute for Disease Modeling. Pathogens and Disease 76(5) (2018).
Perspectives and reviews
Mechanistic within-host models of the asexual Plasmodium falciparum infection: a review and analytical assessment.
Camponovo F., Lee, T.E., Russell, J.R., Burgert L., Gerardin J., and Penny M.A. Malaria Journal 20:309 (2021).
Beyond national indicators: adapting the Demographic and Health Surveys’ sampling strategies and questions to better inform subnational malaria intervention policy.
Ozodiegwu I.D., Ambrose M., Battle K.E., Bever C.A., Diallo O., Galatas B., Runge M., and Gerardin J. Malaria Journal 20:122 (2021).
From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.
Eckhoff P.A., Bever C.A., Gerardin J., Wenger E.A., and Smith D.L. Current Opinion in Insect Science 10,118-23 (2015).
Fun with maths: exploring implications of mathematical models for malaria eradication.
Eckhoff P.A., Bever C.A., Gerardin J., and Wenger, E.A. Malaria Journal 13:486 (2014).
Preprint: Socioeconomic, demographic and environmental factors inform intervention prioritization in urban Nigeria.
Chiziba C., Diallo O., Bertozzi-Villa A., Weiss D., Mercer L., Gerardin J., Ozodiegwu I.D. medRxiv (2022).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Intervention mixes for control and elimination
Modeling impact and cost‐effectiveness of driving‐Y gene drives for malaria elimination in the Democratic Republic of the Congo.
Metchanun N., Borgemeister C., Amzati G., von Braun J., Nikolov M., Selvaraj P., Gerardin J. Evolutionary Applications. 15:132–148 (2022).
Vector genetics, insecticide resistance and gene drives: an agent-based modeling approach to evaluate malaria transmission and elimination.
Selvaraj P., Wenger E.A., Bridenbecker D., Windbichler N., Russell J.R., Gerardin J., Bever C.A., Nikolov M. PLoS Computational Biology. 16(8): e1008121 (2020).
Reducing malaria burden and accelerating elimination with long-lasting systemic insecticides: a modelling study of three potential use cases.
Selvaraj P.*, Suresh J.*, Wenger E.A., Bever C.A., and Gerardin J. Malaria Journal 18:307 (2019).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study.
Gerardin J., Bever C.A., Bridenbecker D., Hamainza B., Silumbe K., Miller J.M., Eisele T.P., Eckhoff P.A., and Wenger E.A. Malaria Journal 16:248 (2017).
Malaria elimination in the Lake Kariba region of Zambia: a spatial dynamical model.
Nikolov M., Bever C.A., Upfill-Brown A., Hamainza B., Miller J.M., Eckhoff P.A., Wenger E.A., and Gerardin J. PLoS Computational Biology 12(11):e1005192 (2016).
Drug-based strategies
Long-term effects of increased adoption of artemisinin combination therapies in Burkina Faso.
Zupko R., Nguyen T.D., Some A.F., Tran T.N., Gerardin J., Dudas P., Giang D.D., Wesolowski A., Ouedraogo J.B., Boni M.F. PLoS Global Public Health 2(2): e0000111 (2022).
Impact of mass drug administration campaigns depends on interaction with seasonal human movement.
Gerardin J., Bertozzi-Villa A., Eckhoff P.A., and Wenger E.A. International Health 10:1 (2018).
Role of mass drug administration in elimination of Plasmodium falciparum malaria: a consensus modelling study.
Brady O.J., Slater H.C., Pemberton-Ross P., Wenger E., Maude R.J., Ghani A.C., Penny M.A., Gerardin J., White L.J., Chitnis N., Aguas R., Hay S.I., Smith D.L., Stuckey E.M., Okiro E.A., Smith T.A., and Okell L.C. Lancet Global Health 5(7):e680 (2017).
Effectiveness of reactive case detection for malaria elimination in three archetypical transmission settings: a modelling study.
Gerardin J., Bever C.A., Bridenbecker D., Hamainza B., Silumbe K., Miller J.M., Eisele T.P., Eckhoff P.A., and Wenger E.A. Malaria Journal 16:248 (2017).
Malaria elimination in the Lake Kariba region of Zambia: a spatial dynamical model.
Nikolov M., Bever C.A., Upfill-Brown A., Hamainza B., Miller J.M., Eckhoff P.A., Wenger E.A., and Gerardin J. PLoS Computational Biology 12(11):e1005192 (2016).
Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission.
Gerardin J., Bever C.A., Hamainza B., Miller J.M., Eckhoff P.A., and Wenger E.A. PLoS Computational Biology 12(1):e1004707 (2016).
Mass campaigns with antimalarial drugs: a modelling comparison of artemether-lumefantrine and DHA-piperaquine with and without primaquine as tools for malaria control and elimination.
Gerardin J., Eckhoff P.A., and Wenger E.A. BMC Infectious Diseases 15:144 (2015).
Infectious reservoir and infection detection
Investigating the impact of enhanced community case management and monthly screening and treatment on the transmissibility of malaria infections in Burkina Faso: study protocol for a cluster-randomised trial
Collins K.A., Ouedraogo A., Guelbeogo W.M., Awandu S.S., Stone W., Soulama I., Ouattara M., Nombre A., Diarra A., Bradley J., Selvaraj P., Gerardin J., Drakeley C., Bousema T., Tiono A.B. BMJ Open. 9:e030598 (2019).
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Optimal population-level infection detection strategies for malaria control and elimination in a spatial model of malaria transmission.
Gerardin J., Bever C.A., Hamainza B., Miller J.M., Eckhoff P.A., and Wenger E.A. PLoS Computational Biology 12(1):e1004707 (2016).
Dynamics of the human infectious reservoir for malaria determined by mosquito feeding assay an ultra-sensitive malaria diagnosis in Burkina Faso.
Ouédraogo A.L., Gonçalves B.P., Gnémé A., Wenger E.A., Guelbeogo M.W., Ouédraogo A., Gerardin J., Bever C.A., Lyons H., Pitroipa X., Verhave J.P., Eckhoff P.A., Drakeley C., Sauerwein R., Luty A.J.F., Kouyaté B., and Bousema T. Journal of Infectious Diseases 213(1):90-99 (2016).
Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness.
Gerardin J., Ouédraogo A.L., McCarthy K.A., Eckhoff P.A., and Wenger E.A. Malaria Journal 14:231 (2015).
Model calibration
Seasonality and heterogeneity of malaria transmission determine success of interventions in high-endemic settings: a modeling study.
Selvaraj P., Wenger E.A., and Gerardin J. BMC Infectious Diseases 18(1):413 (2018).
Characterization of the infectious reservoir of malaria with an agent-based model calibrated to age-stratified parasite densities and infectiousness.
Gerardin J., Ouédraogo A.L., McCarthy K.A., Eckhoff P.A., and Wenger E.A. Malaria Journal 14:231 (2015).
Model development
Implementation and applications of the EMOD individual-based disease modeling platform: software design and development processes to enable multi-scale modeling.
Bershteyn A., Gerardin J., Bridenbecker D., Lorton C., et al. on behalf of the Institute for Disease Modeling. Pathogens and Disease 76(5) (2018).
Perspectives and reviews
Mechanistic within-host models of the asexual Plasmodium falciparum infection: a review and analytical assessment.
Camponovo F., Lee, T.E., Russell, J.R., Burgert L., Gerardin J., and Penny M.A. Malaria Journal 20:309 (2021).
Beyond national indicators: adapting the Demographic and Health Surveys’ sampling strategies and questions to better inform subnational malaria intervention policy.
Ozodiegwu I.D., Ambrose M., Battle K.E., Bever C.A., Diallo O., Galatas B., Runge M., and Gerardin J. Malaria Journal 20:122 (2021).
From puddles to planet: modeling approaches to vector-borne diseases at varying resolution and scale.
Eckhoff P.A., Bever C.A., Gerardin J., Wenger E.A., and Smith D.L. Current Opinion in Insect Science 10,118-23 (2015).
Fun with maths: exploring implications of mathematical models for malaria eradication.
Eckhoff P.A., Bever C.A., Gerardin J., and Wenger, E.A. Malaria Journal 13:486 (2014).
Publications: COVID-19
Modeling robust COVID-19 intensive care unit occupancy thresholds for imposing mitigation to prevent exceeding capacities.
Runge M., Richardson R.A.K., Clay P., Eagan A., Holden T.M., Singam M., Tsuboyama N., Arevalo P., Fornoff J., Patrick S., Ezike N.O., Gerardin J. PLOS Global Public Health (in press 2022).
Structural racism and COVID-19 response: Higher risk of exposure drives disparate COVID-19 deaths among Black and Hispanic/Latinx residents of Illinois, USA.
Holden T.M., Simon M.A., Arnold D.T., Halloway V, Gerardin J. BMC Public Health (2022).
Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020.
Holden T.M.*, Richardson R.A.K.*, Arevalo P., Duffus W.A., Runge M., Whitney E., Wise L., Ezike N.O., Patrick S., Cobey S., Gerardin J. BMC Public Health (2021).
Mobility network modeling explains higher SARS-CoV-2 infection rates among disadvantaged groups and informs reopening strategies.
Chang S.Y.*, Pierson E.*, Koh P.W.*, Gerardin J., Redbird B., Grusky D., Leskovec J. Nature (2021).
Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation.
Armstrong E., Runge M., Gerardin J. Infectious Disease Modelling (2021).
Runge M., Richardson R.A.K., Clay P., Eagan A., Holden T.M., Singam M., Tsuboyama N., Arevalo P., Fornoff J., Patrick S., Ezike N.O., Gerardin J. PLOS Global Public Health (in press 2022).
Structural racism and COVID-19 response: Higher risk of exposure drives disparate COVID-19 deaths among Black and Hispanic/Latinx residents of Illinois, USA.
Holden T.M., Simon M.A., Arnold D.T., Halloway V, Gerardin J. BMC Public Health (2022).
Geographic and demographic heterogeneity of SARS-CoV-2 diagnostic testing in Illinois, USA, March to December 2020.
Holden T.M.*, Richardson R.A.K.*, Arevalo P., Duffus W.A., Runge M., Whitney E., Wise L., Ezike N.O., Patrick S., Cobey S., Gerardin J. BMC Public Health (2021).
Mobility network modeling explains higher SARS-CoV-2 infection rates among disadvantaged groups and informs reopening strategies.
Chang S.Y.*, Pierson E.*, Koh P.W.*, Gerardin J., Redbird B., Grusky D., Leskovec J. Nature (2021).
Identifying the measurements required to estimate rates of COVID-19 transmission, infection, and detection, using variational data assimilation.
Armstrong E., Runge M., Gerardin J. Infectious Disease Modelling (2021).