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 developing a continent-wide expansion plan for seasonal malaria chemoprevention and stratification of high-burden areas for intervention mix planning to reduce malaria morbidity and mortality. We are supported by a grant from the Bill and Melinda Gates Foundation.
For COVID-19, we support Illinois and Chicago departments of public health in making evidence-based policy for COVID-19 containment. We are supported by grants from the NIH via MIDAS and NUCATS as well as an award from the Crown Seed Covid Fund's NU-TAU joint award program. 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 developing a continent-wide expansion plan for seasonal malaria chemoprevention and stratification of high-burden areas for intervention mix planning to reduce malaria morbidity and mortality. We are supported by a grant from the Bill and Melinda Gates Foundation.
For COVID-19, we support Illinois and Chicago departments of public health in making evidence-based policy for COVID-19 containment. We are supported by grants from the NIH via MIDAS and NUCATS as well as an award from the Crown Seed Covid Fund's NU-TAU joint award program. Our COVID-19 outputs and model are publicly available.
Publications: Malaria
Intervention mixes for control and elimination
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).
Mass drug administration
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
Study protocol for a cluster-randomized trial investigating the impact of enhanced community case management and monthly screening and treatment on the transmissibility of malaria infections in Burkina Faso.
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
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).
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).
Mass drug administration
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
Study protocol for a cluster-randomized trial investigating the impact of enhanced community case management and monthly screening and treatment on the transmissibility of malaria infections in Burkina Faso.
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
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
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).
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).