Assessment of Culicidae collection methods for xenomonitoring lymphatic filariasis in malaria co-infection context in Burkina Faso.


Journal

PLoS neglected tropical diseases
ISSN: 1935-2735
Titre abrégé: PLoS Negl Trop Dis
Pays: United States
ID NLM: 101291488

Informations de publication

Date de publication:
29 Mar 2024
Historique:
received: 01 03 2023
accepted: 25 02 2024
medline: 29 3 2024
pubmed: 29 3 2024
entrez: 29 3 2024
Statut: aheadofprint

Résumé

Entomological surveillance of lymphatic filariasis and malaria infections play an important role in the decision-making of national programs to control, or eliminate these both diseases. In areas where both diseases prevalence is low, a large number of mosquitoes need to be sampled to determine vectors infection rate. To do this, efficient mosquito collection methods must be used. This study is part in this framework, to assess appropriate mosquito collection methods for lymphatic filariasis xenomonitoring in a coexistence context with malaria in Burkina Faso. Mosquito collections were performed between August and September 2018 in four villages (Koulpissi, Seiga, and Péribgan, Saptan), distributed in East and South-West health regions of Burkina Faso. Different collection methods were used: Human Landing Catches (HLC) executed indoor and outdoor, Window Exit-Trap, Double Net Trap (DNT) and Pyrethrum Spray Catches (PSC). Molecular analyses were performed to identify Anopheles gambiae s.l. sibling species and to detect Wuchereria bancrofti and Plasmodium falciparum infection in Anopheles mosquitoes. A total of 3 322 mosquitoes were collected among this, Anopheles gambiae s.l. was the vector caught in largest proportion (63.82%). An. gambiae s.l. sibling species molecular characterization showed that An. gambiae was the dominant specie in all villages. The Human Landing Catches (indoor and outdoor) collected the highest proportion of mosquitoes (between 61.5% and 82.79%). For the sampling vectors infected to W. bancrofti or P. falciparum, PSC, HLC and Window Exit-Trap were found the most effective collection methods. This study revealed that HLC indoor and outdoor remained the most effective collection method. Likewise, the results showed the probability to use Window Exit-Trap and PSC collection methods to sample Anopheles infected.

Sections du résumé

BACKGROUND BACKGROUND
Entomological surveillance of lymphatic filariasis and malaria infections play an important role in the decision-making of national programs to control, or eliminate these both diseases. In areas where both diseases prevalence is low, a large number of mosquitoes need to be sampled to determine vectors infection rate. To do this, efficient mosquito collection methods must be used. This study is part in this framework, to assess appropriate mosquito collection methods for lymphatic filariasis xenomonitoring in a coexistence context with malaria in Burkina Faso.
METHODOLOGY/PRINCIPAL FINDINGS RESULTS
Mosquito collections were performed between August and September 2018 in four villages (Koulpissi, Seiga, and Péribgan, Saptan), distributed in East and South-West health regions of Burkina Faso. Different collection methods were used: Human Landing Catches (HLC) executed indoor and outdoor, Window Exit-Trap, Double Net Trap (DNT) and Pyrethrum Spray Catches (PSC). Molecular analyses were performed to identify Anopheles gambiae s.l. sibling species and to detect Wuchereria bancrofti and Plasmodium falciparum infection in Anopheles mosquitoes. A total of 3 322 mosquitoes were collected among this, Anopheles gambiae s.l. was the vector caught in largest proportion (63.82%). An. gambiae s.l. sibling species molecular characterization showed that An. gambiae was the dominant specie in all villages. The Human Landing Catches (indoor and outdoor) collected the highest proportion of mosquitoes (between 61.5% and 82.79%). For the sampling vectors infected to W. bancrofti or P. falciparum, PSC, HLC and Window Exit-Trap were found the most effective collection methods.
CONCLUSIONS/SIGNIFICANCE CONCLUSIONS
This study revealed that HLC indoor and outdoor remained the most effective collection method. Likewise, the results showed the probability to use Window Exit-Trap and PSC collection methods to sample Anopheles infected.

Identifiants

pubmed: 38551982
doi: 10.1371/journal.pntd.0012021
pii: PNTD-D-23-00279
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e0012021

Informations de copyright

Copyright: © 2024 Coulibaly et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Déclaration de conflit d'intérêts

The authors declare that they have no competing interests.

Auteurs

Sanata Coulibaly (S)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Simon P Sawadogo (SP)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Achille S Nikièma (AS)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Aristide S Hien (AS)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Rabila Bamogo (R)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Lassane Koala (L)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Ibrahim Sangaré (I)

Université Nazi Boni, Bobo-Dioulasso, Burkina Faso.

Roland W Bougma (RW)

Programme National de Lutte contre les Maladies Tropicales Négligées, Ministère de la Santé, Ouagadougou, Burkina Faso.

Benjamin Koudou (B)

Centre Suisse de Recherches Scientifiques, Université Félix-Houphouët-Boigny, Abidjan, Côte d'Ivoire.

Florence Fournet (F)

MIVEGEC (UM, IRD, CNRS) Montpellier, France.

Georges A Ouédraogo (GA)

Université Nazi Boni, Bobo-Dioulasso, Burkina Faso.

Roch K Dabiré (RK)

Institut de Recherche en Sciences de la Santé (IRSS), Bobo-Dioulasso, Burkina Faso.

Classifications MeSH