Patterns of human exposure to malaria vectors in Zanzibar and implications for malaria elimination efforts

Abstract

Background: Zanzibar provides a good case study for malaria elimination. The islands have experienced a dramatic reduction in malaria burden since the introduction of effective vector control interventions and case management. Malaria prevalence has now been maintained below 1% for the past decade and the islands can feasibly aim for elimination. Methods: To better understand factors that may contribute to remaining low-level malaria transmission in Zanzibar, layered human behavioural and entomological research was conducted between December 2016 and December 2017 in 135 randomly selected households across six administrative wards. The study included: (1) household surveys, (2) structured household observations of nighttime activity and sleeping patterns, and (3) paired indoor and outdoor mosquito collections. Entomological and human behavioural data were integrated to provide weighted estimates of exposure to vector bites, accounting for proportions of people indoors or outdoors, and protected by insecticidetreated nets (ITNs) each hour of the night. Results: Overall, 92% of female Anopheles mosquitoes were caught in the rainy season compared to 8% in the dry season and 72% were caught outdoors compared to 28% indoors. For individual ITN users, ITNs prevented an estimated two-thirds (66%) of exposure to vector bites and nearly three quarters (73%) of residual exposure was estimated to occur outdoors. Based on observed levels of ITN use in the study sites, the population-wide mean personal protection provided by ITNs was 42%. Discussion/conclusions: This study identified gaps in malaria prevention in Zanzibar with results directly applicable for improving ongoing programme activities. While overall biting risk was low, the most notable finding was that current levels of ITN use are estimated to prevent less than half of exposure to malaria vector bites. Variation in ITN use across sites and seasons suggests that additional gains could be made through targeted social and behaviour change interventions. However, even for ITN users, gaps in protection remain, with a majority of exposure to vector bites occurring outdoors before going to sleep. Supplemental interventions targeting outdoor exposure to malaria vectors, and groups that may be at increased risk of exposure to malaria vectors, should be explored.

Quantifying and characterizing hourly human exposure to malaria vectors bites to address residual malaria transmission during dry and rainy seasons in rural Southwest Burkina Faso

“…where and when residual transmission is expected to occur. Numerous studies have used this model in Africa [15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30]. However until now, only one of these studies has reported exposure estimates for sites located in Burkina Faso [18].…”

Reduced human-biting preferences of the African malaria vectors Anopheles arabiensis and Anopheles gambiae in an urban context: Controlled, competitive host-preference experiments in Tanzania

“…Apart from the distributions of bites between inside and outsides the houses and at different times of the night [1,2], what mosquitoes feed upon critically determines the choice and impact of human-targeted vector control interventions [3][4][5][6][7][8]. For example, both historical and recent reports [9][10][11][12][13][14] show that the widespread use of long-lasting insecticide-treated nets (LLNs) or indoor residual spraying (IRS), which directly target humans or houses they live in, strongly suppressed or virtually eliminated the population of the main malaria vectors Anopheles gambiae sensu stricto, and Anopheles funestus sensu stricto.…”

Improved Use of Drone Imagery for Malaria Vector Control through Technology-Assisted Digitizing (TAD)

“…If a false classification was made, a record was made of the correct class. The classification points were used to construct an error matrix for each site, which was subsequently used to calculate accuracy statistics, including % overall accuracy, kappa coefficient and quantity and allocation disagreement scores [30].…”