Spatial and temporal village-level prevalence of Plasmodium infection and associated risk factors in two districts of Meghalaya, India.


Journal

Malaria journal
ISSN: 1475-2875
Titre abrégé: Malar J
Pays: England
ID NLM: 101139802

Informations de publication

Date de publication:
04 Feb 2021
Historique:
received: 09 12 2020
accepted: 20 01 2021
entrez: 5 2 2021
pubmed: 6 2 2021
medline: 10 8 2021
Statut: epublish

Résumé

Despite declining incidence over the past decade, malaria remains an important health burden in India. This study aimed to assess the village-level temporal patterns of Plasmodium infection in two districts of the north-eastern state of Meghalaya and evaluate risk factors that might explain these patterns. Primary Health Centre passive malaria case data from 2014 to 2018 were analysed to characterize village-specific annual incidence and temporal trends. Active malaria case detection was undertaken in 2018 and 2019 to detect Plasmodium infections using PCR. A questionnaire collected socio-demographic, environmental, and behavioural data, and households were spatially mapped via GPS. Adult mosquitoes were sampled at a subset of subjects' houses, and Anopheles were identified by PCR and sequencing. Risk factors for Plasmodium infection were evaluated using bivariate and multivariate logistic regression analysis, and spatial cluster analysis was undertaken. The annual malaria incidence from PHC-based passive surveillance datasets in 2014-2018 was heterogenous but declining across villages in both districts. Active surveillance in 2018 enrolled 1468 individuals from 468 households (West Jaintia Hills) and 1274 individuals from 359 households (West Khasi Hills). Plasmodium falciparum prevalence per 100 people varied from 0 to 4.1% in the nine villages of West Jaintia Hills, and from 0 to 10.6% in the 12 villages of West Khasi Hills. Significant clustering of P. falciparum infections [observed = 11, expected = 2.15, Relative Risk (RR) = 12.65; p < 0.001] was observed in West Khasi Hills. A total of 13 Anopheles species were found at 53 houses in five villages, with Anopheles jeyporiensis being the most abundant. Risk of infection increased with presence of mosquitoes and electricity in the households [Odds Ratio (OR) = 1.19 and 1.11], respectively. Households with reported animals had reduced infection risk (OR = 0.91). Malaria incidence during 2014-2018 declined in all study villages covered by the passive surveillance data, a period that includes the first widespread insecticide-treated net campaign. The survey data from 2018 revealed a significant association between Plasmodium infection and certain household characteristics. Since species of Plasmodium-competent mosquito vectors continue to be abundant, malaria resurgence remains a threat, and control efforts should continue.

Sections du résumé

BACKGROUND BACKGROUND
Despite declining incidence over the past decade, malaria remains an important health burden in India. This study aimed to assess the village-level temporal patterns of Plasmodium infection in two districts of the north-eastern state of Meghalaya and evaluate risk factors that might explain these patterns.
METHODS METHODS
Primary Health Centre passive malaria case data from 2014 to 2018 were analysed to characterize village-specific annual incidence and temporal trends. Active malaria case detection was undertaken in 2018 and 2019 to detect Plasmodium infections using PCR. A questionnaire collected socio-demographic, environmental, and behavioural data, and households were spatially mapped via GPS. Adult mosquitoes were sampled at a subset of subjects' houses, and Anopheles were identified by PCR and sequencing. Risk factors for Plasmodium infection were evaluated using bivariate and multivariate logistic regression analysis, and spatial cluster analysis was undertaken.
RESULTS RESULTS
The annual malaria incidence from PHC-based passive surveillance datasets in 2014-2018 was heterogenous but declining across villages in both districts. Active surveillance in 2018 enrolled 1468 individuals from 468 households (West Jaintia Hills) and 1274 individuals from 359 households (West Khasi Hills). Plasmodium falciparum prevalence per 100 people varied from 0 to 4.1% in the nine villages of West Jaintia Hills, and from 0 to 10.6% in the 12 villages of West Khasi Hills. Significant clustering of P. falciparum infections [observed = 11, expected = 2.15, Relative Risk (RR) = 12.65; p < 0.001] was observed in West Khasi Hills. A total of 13 Anopheles species were found at 53 houses in five villages, with Anopheles jeyporiensis being the most abundant. Risk of infection increased with presence of mosquitoes and electricity in the households [Odds Ratio (OR) = 1.19 and 1.11], respectively. Households with reported animals had reduced infection risk (OR = 0.91).
CONCLUSION CONCLUSIONS
Malaria incidence during 2014-2018 declined in all study villages covered by the passive surveillance data, a period that includes the first widespread insecticide-treated net campaign. The survey data from 2018 revealed a significant association between Plasmodium infection and certain household characteristics. Since species of Plasmodium-competent mosquito vectors continue to be abundant, malaria resurgence remains a threat, and control efforts should continue.

Identifiants

pubmed: 33541366
doi: 10.1186/s12936-021-03600-w
pii: 10.1186/s12936-021-03600-w
pmc: PMC7859895
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

70

Subventions

Organisme : NIAID NIH HHS
ID : U19 AI089676
Pays : United States
Organisme : National Institute of Allergy and Infectious Diseases
ID : U19AI08967

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Auteurs

Anne Kessler (A)

Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, 10003, USA.

Badondor Shylla (B)

Indian Institute of Public Health-Shillong, Shillong, Meghalaya, 793001, India.
Martin Luther Christian University, Shillong, Meghalaya, 793006, India.

Upasana Shyamsunder Singh (US)

Department of Earth and Environmental Sciences, School of Natural Sciences, University of Manchester, Manchester, M13 9PT, UK.

Rilynti Lyngdoh (R)

Department of Health Services (Malaria), National Vector Borne Disease Programme, Lawmali, Pasteur Hill, Shillong, Meghalaya, 793001, India.

Bandapkupar Mawkhlieng (B)

Indian Institute of Public Health-Shillong, Shillong, Meghalaya, 793001, India.

Anna Maria van Eijk (AM)

Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, 10003, USA.

Steven A Sullivan (SA)

Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, 10003, USA.

Aparup Das (A)

ICMR-National Institute of Research in Tribal Health, Jabalpur, Madhya Pradesh, 482003, India.

Catherine Walton (C)

Department of Earth and Environmental Sciences, School of Natural Sciences, University of Manchester, Manchester, M13 9PT, UK.

Mark L Wilson (ML)

Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109, USA.

Jane M Carlton (JM)

Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY, 10003, USA. jane.carlton@nyu.edu.
Department of Epidemiology, College of Global Public Health, New York University, New York, NY, 10012, USA. jane.carlton@nyu.edu.

Sandra Albert (S)

Indian Institute of Public Health-Shillong, Shillong, Meghalaya, 793001, India. sandra.albert@phfi.org.
Martin Luther Christian University, Shillong, Meghalaya, 793006, India. sandra.albert@phfi.org.

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