» Articles » PMID: 22624853

An Affordable, Quality-assured Community-based System for High-resolution Entomological Surveillance of Vector Mosquitoes That Reflects Human Malaria Infection Risk Patterns

Overview
Journal Malar J
Publisher Biomed Central
Specialty Tropical Medicine
Date 2012 May 26
PMID 22624853
Citations 31
Authors
Affiliations
Soon will be listed here.
Abstract

Background: More sensitive and scalable entomological surveillance tools are required to monitor low levels of transmission that are increasingly common across the tropics, particularly where vector control has been successful. A large-scale larviciding programme in urban Dar es Salaam, Tanzania is supported by a community-based (CB) system for trapping adult mosquito densities to monitor programme performance.

Methodology: An intensive and extensive CB system for routine, longitudinal, programmatic surveillance of malaria vectors and other mosquitoes using the Ifakara Tent Trap (ITT-C) was developed in Urban Dar es Salaam, Tanzania, and validated by comparison with quality assurance (QA) surveys using either ITT-C or human landing catches (HLC), as well as a cross-sectional survey of malaria parasite prevalence in the same housing compounds.

Results: Community-based ITT-C had much lower sensitivity per person-night of sampling than HLC (Relative Rate (RR) [95% Confidence Interval (CI)] = 0.079 [0.051, 0.121], P < 0.001 for Anopheles gambiae s.l. and 0.153 [0.137, 0.171], P < 0.001 for Culicines) but only moderately differed from QA surveys with the same trap (0.536 [0.406,0.617], P = 0.001 and 0.747 [0.677,0.824], P < 0.001, for An. gambiae or Culex respectively). Despite the poor sensitivity of the ITT per night of sampling, when CB-ITT was compared with QA-HLC, it proved at least comparably sensitive in absolute terms (171 versus 169 primary vectors caught) and cost-effective (153US$ versus 187US$ per An. gambiae caught) because it allowed more spatially extensive and temporally intensive sampling (4284 versus 335 trap nights distributed over 615 versus 240 locations with a mean number of samples per year of 143 versus 141). Despite the very low vectors densities (Annual estimate of about 170 An gambiae s.l bites per person per year), CB-ITT was the only entomological predictor of parasite infection risk (Odds Ratio [95% CI] = 4.43[3.027,7. 454] per An. gambiae or Anopheles funestus caught per night, P =0.0373).

Discussion And Conclusion: CB trapping approaches could be improved with more sensitive traps, but already offer a practical, safe and affordable system for routine programmatic mosquito surveillance and clusters could be distributed across entire countries by adapting the sample submission and quality assurance procedures accordingly.

Citing Articles

Empowering rural communities for effective larval source management: A small-scale field evaluation of a community-led larviciding approach to control malaria in south-eastern Tanzania.

Mapua S, Limwagu A, Kishkinev D, Kifungo K, Nambunga I, Mziray S Parasite Epidemiol Control. 2024; 27:e00382.

PMID: 39434900 PMC: 11493201. DOI: 10.1016/j.parepi.2024.e00382.


Evaluation of community-based vector surveillance system for routine entomological monitoring under low malaria vector densities and high bed net coverage in western Kenya.

Abongo B, Stanton M, Donnelly M, Ochomo E, Kuile F, Samuels A Malar J. 2023; 22(1):203.

PMID: 37400805 PMC: 10318638. DOI: 10.1186/s12936-023-04629-9.


What incentives encourage local communities to collect and upload mosquito sound data by using smartphones? A mixed methods study in Tanzania.

Dam R, Mponzi W, Msaky D, Mwandyala T, Kaindoa E, Sinka M Glob Health Res Policy. 2023; 8(1):18.

PMID: 37246227 PMC: 10226264. DOI: 10.1186/s41256-023-00298-y.


Which trap is best? Alternatives to outdoor human landing catches for malaria vector surveillance: a meta-analysis.

Eckert J, Oladipupo S, Wang Y, Jiang S, Patil V, McKenzie B Malar J. 2022; 21(1):378.

PMID: 36494724 PMC: 9733232. DOI: 10.1186/s12936-022-04332-1.


Costs and Cost-Effectiveness of Malaria Control Interventions: A Systematic Literature Review.

Conteh L, Shuford K, Agboraw E, Kont M, Kolaczinski J, Patouillard E Value Health. 2021; 24(8):1213-1222.

PMID: 34372987 PMC: 8324482. DOI: 10.1016/j.jval.2021.01.013.


References
1.
Killeen G, Tanner M, Mukabana W, Kalongolela M, Kannady K, Lindsay S . Habitat targeting for controlling aquatic stages of malaria vectors in Africa. Am J Trop Med Hyg. 2006; 74(4):517-8. View

2.
Majambere S, Lindsay S, Green C, Kandeh B, Fillinger U . Microbial larvicides for malaria control in The Gambia. Malar J. 2007; 6:76. PMC: 1899511. DOI: 10.1186/1475-2875-6-76. View

3.
Chaki P, Dongus S, Fillinger U, Kelly A, Killeen G . Community-owned resource persons for malaria vector control: enabling factors and challenges in an operational programme in Dar es Salaam, United Republic of Tanzania. Hum Resour Health. 2011; 9:21. PMC: 3204271. DOI: 10.1186/1478-4491-9-21. View

4.
Fillinger U, Ndenga B, Githeko A, Lindsay S . Integrated malaria vector control with microbial larvicides and insecticide-treated nets in western Kenya: a controlled trial. Bull World Health Organ. 2009; 87(9):655-65. PMC: 2739910. DOI: 10.2471/blt.08.055632. View

5.
Bejon P, Williams T, Liljander A, Noor A, Wambua J, Ogada E . Stable and unstable malaria hotspots in longitudinal cohort studies in Kenya. PLoS Med. 2010; 7(7):e1000304. PMC: 2897769. DOI: 10.1371/journal.pmed.1000304. View