Public health impact of the spread of Anopheles stephensi in the WHO Eastern Mediterranean Region countries in Horn of Africa and Yemen: need for integrated vector surveillance and control.

BACKGROUND: Anopheles stephensi is an efficient vector of both Plasmodium falciparum and Plasmodium vivax in South Asia and the Middle East. The spread of An. stephensi to countries within the Horn of Africa threatens progress in malaria control in this region as well as the rest of sub-Saharan Africa. METHODS: The available malaria data and the timeline for the detection of An. stephensi was reviewed to analyse the role of An. stephensi in malaria transmission in Horn of Africa of the Eastern Mediterranean Region (EMR) in Djibouti, Somalia, Sudan and Yemen. RESULTS: Malaria incidence in Horn of Africa of EMR and Yemen, increased from 41.6 in 2015 to 61.5 cases per 1000 in 2020. The four countries from this region, Djibouti, Somalia, Sudan and Yemen had reported the detection of An. stephensi as of 2021. In Djibouti City, following its detection in 2012, the estimated incidence increased from 2.5 cases per 1000 in 2013 to 97.6 cases per 1000 in 2020. However, its contribution to malaria transmission in other major cities and in other countries, is unclear because of other factors, quality of the urban malaria data, human mobility, uncertainty about the actual arrival time of An. stephensi and poor entomological surveillance. CONCLUSIONS: While An. stephensi may explain a resurgence of malaria in Djibouti, further investigations are needed to understand its interpretation trends in urban malaria across the greater region. More investment for multisectoral approach and integrated surveillance and control should target all vectors particularly malaria and dengue vectors to guide interventions in urban areas.

Using non-exceedance probabilities of policy-relevant malaria prevalence thresholds to identify areas of low transmission in Somalia.

BACKGROUND: Countries planning malaria elimination must adapt from sustaining universal control to targeted intervention and surveillance. Decisions to make this transition require interpretable information, including malaria parasite survey data. As transmission declines, observed parasite prevalence becomes highly heterogeneous with most communities reporting estimates close to zero. Absolute estimates of prevalence become hard to interpret as a measure of transmission intensity and suitable statistical methods are required to handle uncertainty of area-wide predictions that are programmatically relevant. METHODS: A spatio-temporal geostatistical binomial model for Plasmodium falciparum prevalence (PfPR) was developed using data from cross-sectional surveys conducted in Somalia in 2005, 2007-2011 and 2014. The fitted model was then used to generate maps of non-exceedance probabilities, i.e. the predictive probability that the region-wide population-weighted average PfPR for children between 2 and 10 years (PfPR2-10) lies below 1 and 5%. A comparison was carried out with the decision-making outcomes from those of standard approaches that ignore uncertainty in prevalence estimates. RESULTS: By 2010, most regions in Somalia were at least 70% likely to be below 5% PfPR2-10 and, by 2014, 17 regions were below 5% PfPR2-10 with a probability greater than 90%. Larger uncertainty is observed using a threshold of 1%. By 2011, only two regions were more than 90% likely of being < 1% PfPR2-10 and, by 2014, only three regions showed such low level of uncertainty. The use of non-exceedance probabilities indicated that there was weak evidence to classify 10 out of the 18 regions as < 1% in 2014, when a greater than 90% non-exceedance probability was required. CONCLUSION: Unlike standard approaches, non-exceedance probabilities of spatially modelled PfPR2-10 allow to quantify uncertainty of prevalence estimates in relation to policy relevant intervention thresholds, providing programmatically relevant metrics to make decisions on transitioning from sustained malaria control to strategies that encompass methods of malaria elimination.