Simulation of malaria epidemiology and control in the highlands of western Kenya

Abstract

BackgroundModels of Plasmodium falciparum malaria epidemiology that provide realistic quantitative predictions of likely epidemiological outcomes of existing vector control strategies have the potential to assist in planning for the control and elimination of malaria. This work investigates the applicability of mathematical modelling of malaria transmission dynamics in Rachuonyo South, a district with low, unstable transmission in the highlands of western Kenya.MethodsIndividual-based stochastic simulation models of malaria in humans and a deterministic model of malaria in mosquitoes as part of the OpenMalaria platform were parameterized to create a scenario for the study area based on data from ongoing field studies and available literature. The scenario was simulated for a period of two years with a population of 10,000 individuals and validated against malaria survey data from Rachuonyo South. Simulations were repeated with multiple random seeds and an ensemble of 14 model variants to address stochasticity and model uncertainty. A one-dimensional sensitivity analysis was conducted to address parameter uncertainty.ResultsThe scenario was able to reproduce the seasonal pattern of the entomological inoculation rate (EIR) and patent infections observed in an all-age cohort of individuals sampled monthly for one year. Using an EIR estimated from serology to parameterize the scenario resulted in a closer fit to parasite prevalence than an EIR estimated using entomological methods. The scenario parameterization was most sensitive to changes in the timing and effectiveness of indoor residual spraying (IRS) and the method used to detect P. falciparum in humans. It was less sensitive than expected to changes in vector biting behaviour and climatic patterns.ConclusionsThe OpenMalaria model of P. falciparum transmission can be used to simulate the impact of different combinations of current and potential control interventions to help plan malaria control in this low transmission setting. In this setting and for these scenarios, results were highly sensitive to transmission, vector exophagy, exophily and susceptibility to IRS, and the detection method used for surveillance. The level of accuracy of the results will thus depend upon the precision of estimates for each. New methods for analysing and evaluating uncertainty in simulation results will enhance the usefulness of simulations for malaria control decision-making. Improved measurement tools and increased primary data collection will enhance model parameterization and epidemiological monitoring. Further research is needed on the relationship between malaria indices to identify the best way to quantify transmission in low transmission settings. Measuring EIR through mosquito collection may not be the optimal way to estimate transmission intensity in areas with low, unstable transmission.

The impact of hotspot-targeted interventions on malaria transmission: study protocol for a cluster-randomized controlled trial

“…The predominant ethnicity in Rachuonyo is Luo. Local residents depend upon farming, cattle and goat herding for subsistence [23]. Compounds comprise an average of two houses (25th to 75th percentile 1 to 3) and are distributed broadly across a rolling landscape intersected with small streams and rivers.…”

“…Malaria transmission is seasonal, with two peaks in malaria cases reflecting the bimodal rainfall pattern; a peak corresponding to the heaviest rainfall typically occurs between March and June and there is a smaller peak between October and November each year. Most malaria is caused by Plasmodium falciparum [23]. Community cross-sectional surveys conducted in 2010 indicated parasite prevalence averaging 14.8% in the general population but varying between localities from 0% and 51.5%.…”

Towards malaria control and elimination in Ghana: challenges and decision making tools to guide planning

“…Some investigated malaria transmission dynamics in mosquitoes and humans,[43–45] others were used to evaluate the impact of interventions against the disease [43,46] and other models tested the adequacy of age structure in explaining transmission of disease and the impact of varying transmission settings. [35,43,47] The effect of migration on the transmission of malaria have also been modelled in Kenya.…”

Molecular Characterization Reveals Diverse and Unknown Malaria Vectors in the Western Kenyan Highlands

“…This project sought to improve tools for evaluating malaria transmission and control in diverse transmission environments. 37 The MTC studies in the Kenya highlands have included entomological surveys that evaluate biting behavior, compare trapping techniques, and assess the impact of interventions in the highlands of Ranchuonyo and Kisii districts, western Kenya. 40 Adult mosquitoes were collected using Centers for Disease Control and Prevention (CDC) miniature light traps set indoors and outdoors with either standard or ultraviolet bulbs.…”

“…The western Kenyan highlands is an area of unstable, sometimes epidemic malaria 34 where anopheline vector dynamics determine the spread and maintenance of malaria transmission. [35][36][37] The aim of our study was to identify Anopheles species present in two neighboring districts in the western Kenyan highlands using both molecular and morphological tools. This study expands upon previously reported findings of unknown and potentially new vector species in Kisii district, 38 detailing the rDNA ITS2 and mtDNA CO1 regions, and includes sequence analysis of two more recent sets of mosquito collections from an area in the neighboring district, Rachuonyo South.…”