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Correlations between household occupancy and malaria vector biting risk in rural Tanzanian villages: implications for high-resolution spatial targeting of control interventions

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Kaindoa, Emmanuel W., Mkandawile, Gustav, Ligamba, Godfrey, Kelly-Hope, Louise ORCID: https://orcid.org/0000-0002-3330-7629 and Okumu, Fredros O. (2016) 'Correlations between household occupancy and malaria vector biting risk in rural Tanzanian villages: implications for high-resolution spatial targeting of control interventions'. Malaria Journal, Vol 15, Issue 1.

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Abstract

Background:
Fine-scale targeting of interventions is increasingly important where epidemiological disease profiles depict high geographical stratifications. This study verified correlations between household biomass and mosquito house-entry using experimental hut studies, and then demonstrated how geographical foci of mosquito biting risk can be readily identified based on spatial distributions of household occupancies in villages.

Methods:
A controlled 4 × 4 Latin square experiment was conducted in rural Tanzania, in which no, one, three or six adult male volunteers slept under intact bed nets, in experimental huts. Mosquitoes entering the huts were caught using exit interception traps on eaves and windows. Separately, monthly mosquito collections were conducted in 96 randomly selected households in three villages using CDC light traps between March-2012 and November-2013. The number of people sleeping in the houses and other household and environmental characteristics were recorded. ArcGIS 10 (ESRI-USA) spatial analyst tool, Gi* Ord Statistic was used to analyse clustering of vector densities and household occupancy.

Results:
The densities of all mosquito genera increased in huts with one, three or six volunteers, relative to huts with no volunteers, and direct linear correlations within tested ranges (P < 0.001). Significant geographical clustering of indoor densities of malaria vectors, Anopheles arabiensis and Anopheles funestus, but not Culex or Mansonia species occurred in locations where households with highest occupancy were also most clustered (Gi* P ≤ 0.05, and Gi* Z-score ≥1.96).

Conclusions:
This study demonstrates strong correlations between household occupancy and malaria vector densities in households, but also spatial correlations of these variables within and between villages in rural southeastern Tanzania. Fine-scale clustering of indoor densities of vectors within and between villages occurs in locations where houses with highest occupancy are also clustered. The study indicates potential for using household census data to preliminarily identify households with greatest Anopheles mosquito biting risk.

Item Type: Article
Subjects: QX Parasitology > Insects. Other Parasites > QX 510 Mosquitoes
QX Parasitology > Insects. Other Parasites > QX 515 Anopheles
WC Communicable Diseases > Tropical and Parasitic Diseases > WC 750 Malaria
WC Communicable Diseases > Tropical and Parasitic Diseases > WC 765 Prevention and control
Faculty: Department: Biological Sciences > Department of Tropical Disease Biology
Digital Object Identifer (DOI): https://doi.org/10.1186/s12936-016-1268-8
Depositing User: Jessica Jones
Date Deposited: 14 Apr 2016 10:49
Last Modified: 06 Sep 2019 10:55
URI: https://archive.lstmed.ac.uk/id/eprint/5844

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