Defining the relationship between infection prevalence and clinical incidence of Plasmodium falciparum malaria.
In many countries health system data remain too weak to accurately enumerate Plasmodium falciparum malaria cases. In response, cartographic approaches have been developed that link maps of infection prevalence with mathematical relationships to predict the incidence rate of clinical malaria. Microsimulation (or 'agent-based') models represent a powerful new paradigm for defining such relationships; however, differences in model structure and calibration data mean that no consensus yet exists on the optimal form for use in disease-burden estimation. Here we develop a Bayesian statistical procedure combining functional regression-based model emulation with Markov Chain Monte Carlo sampling to calibrate three selected microsimulation models against a purpose-built data set of age-structured prevalence and incidence counts. This allows the generation of ensemble forecasts of the prevalence-incidence relationship stratified by age, transmission seasonality, treatment level and exposure history, from which we predict accelerating returns on investments in large-scale intervention campaigns as transmission and prevalence are progressively reduced.
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Ewan
E
Cameron
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Katherine E
KE
Battle
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Samir
S
Bhatt
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Daniel J
DJ
Weiss
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Donal
D
Bisanzio
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Bonnie
http://orcid.org/0000-0002-1205-719X
B
Mappin
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Ursula
U
Dalrymple
Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK.|Institute for Health Metrics and Evaluation, University of Washington, Seattle, Washington 98121, USA.|Fogarty International Center, National Institutes of Health, Bethesda, Maryland 20892, USA.
Simon I
http://orcid.org/0000-0002-0611-7272
SI
Hay
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
David L
http://orcid.org/0000-0003-4367-3849
DL
Smith
Department of Infectious Disease Epidemiology, MRC Centre for Outbreak Analysis and Modelling, Imperial College London, London W2 1PG, UK.
Jamie T
JT
Griffin
Institute for Disease Modeling, 1555 132nd Avenue NE, Bellevue, Washington 98005, USA.
Edward A
EA
Wenger
Institute for Disease Modeling, 1555 132nd Avenue NE, Bellevue, Washington 98005, USA.
Philip A
PA
Eckhoff
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, University of Basel, Basel 4002, Switzerland.
Thomas A
TA
Smith
Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, University of Basel, Basel 4002, Switzerland.
Melissa A
MA
Penny
Department of Zoology, Spatial Ecology and Epidemiology Group, University of Oxford, Tinbergen Building, Oxford OX1 3PS, UK.
Peter W
PW
Gething
D000293:Adolescent; D000328:Adult; D000349:Africa / Q000453:epidemiology; D000368:Aged; D000369:Aged, 80 and over; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D006801:Humans; D015994:Incidence; D007223:Infant; D007231:Infant, Newborn; D016778:Malaria, Falciparum / Q000453:epidemiology* / Q000635:transmission; D008390:Markov Chains; D008875:Middle Aged; D015233:Models, Statistical; D009010:Monte Carlo Method; D015995:Prevalence; D055815:Young Adult