Predicting factors for malaria re-introduction: an applied model in an elimination setting to prevent malaria outbreaks

Abstract

BackgroundMalaria re-introduction is a challenge in elimination settings. To prevent re-introduction, receptivity, vulnerability, and health system capacity of foci should be monitored using appropriate tools. This study aimed to design an applicable model to monitor predicting factors of re-introduction of malaria in highly prone areas.MethodsThis exploratory, descriptive study was conducted in a pre-elimination setting with a high-risk of malaria transmission re-introduction. By using nominal group technique and literature review, a list of predicting indicators for malaria re-introduction and outbreak was defined. Accordingly, a checklist was developed and completed in the field for foci affected by re-introduction and for cleared-up foci as a control group, for a period of 12 weeks before re-introduction and for the same period in the previous year. Using field data and analytic hierarchical process (AHP), each variable and its sub-categories were weighted, and by calculating geometric means for each sub-category, score of corresponding cells of interaction matrices, lower and upper threshold of different risks strata, including low and mild risk of re-introduction and moderate and high risk of malaria outbreaks, were determined. The developed predictive model was calibrated through resampling with different sets of explanatory variables using R software. Sensitivity and specificity of the model were calculated based on new samples.ResultsTwenty explanatory predictive variables of malaria re-introduction were identified and a predictive model was developed. Unpermitted immigrants from endemic neighbouring countries were determined as a pivotal factor (AHP score: 0.181). Moreover, quality of population movement (0.114), following malaria transmission season (0.088), average daily minimum temperature in the previous 8 weeks (0.062), an outdoor resting shelter for vectors (0.045), and rainfall (0.042) were determined. Positive and negative predictive values of the model were 81.8 and 100 %, respectively.ConclusionsThis study introduced a new, simple, yet reliable model to forecast malaria re-introduction and outbreaks eight weeks in advance in pre-elimination and elimination settings. The model incorporates comprehensive deterministic factors that can easily be measured in the field, thereby facilitating preventive measures.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-016-1192-y) contains supplementary material, which is available to authorized users.

Influx of diverse, drug resistant and transmissible Plasmodium falciparum into a malaria-free setting in Gulf Cooperation (GCC) countries.

“…Low-density gametocytes can readily infect Anopheles, even at sub-microscopical levels [37,38]. Secondary transmission, originating from imported malaria, is often reported in GCC countries in areas where the Anopheles vector is present and a favorable ecological habitat prevails [3,39] Although the resumption of endemic transmission in GCC countries is unlikely, the high rate of imported malaria can readily seed outbreaks in receptive areas, if vector control wanes [3].…”

malERA: An updated research agenda for combination interventions and modelling in malaria elimination and eradication

“…In order to direct interventions, models must incorporate both the risk of importation and the risk for the reestablishment of local transmission [ 165 – 173 ]. The risk of malaria transmission reestablishment can be measured as a function of selected host, vector, and environmental data [ 156 , 170 , 171 , 174 ].…”

“…In order to direct interventions, models must incorporate both the risk of importation and the risk for the reestablishment of local transmission [ 165 – 173 ]. The risk of malaria transmission reestablishment can be measured as a function of selected host, vector, and environmental data [ 156 , 170 , 171 , 174 ]. For example, measures might include human use of insecticide-treated bed nets or indoor residual spraying, mosquito habitat suitability and its link to abundance, and climatic conditions (e.g., temperature, rainfall, and vegetation index measures) that support or accelerate vector and parasite development.…”

Using health facility-based serological surveillance to predict receptive areas at risk of malaria outbreaks in elimination areas

“…Resurgence of malaria is often associated with imported infections and/or P. vivax relapsing infections in areas that remain highly receptive to malaria [13][14][15][16]. Studies have demonstrated the usefulness of spatially referenced entomological data to characterise the heterogeneity of malaria receptivity in areas approaching elimination to prevent outbreaks in the future [17][18][19].…”