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Households or Hotspots? Defining Intervention Targets for Malaria Elimination in Ratanakiri Province, Eastern Cambodia.
Bannister-Tyrrell, Melanie; Krit, Meryam; Sluydts, Vincent; Tho, Sochantha; Sokny, Mao; Mean, Vanna; Kim, Saorin; Menard, Didier; Grietens, Koen Peeters; Abrams, Steven; Hens, Niel; Coosemans, Marc; Bassat, Quique; van Hensbroek, Michael Boele; Durnez, Lies; Van Bortel, Wim.
Afiliação
  • Bannister-Tyrrell M; Institute of Tropical Medicine, Antwerp.
  • Krit M; Institute of Tropical Medicine, Antwerp.
  • Sluydts V; Institute of Tropical Medicine, Antwerp.
  • Tho S; University of Antwerp, Belgium.
  • Sokny M; National Center for Parasitology, Entomology and Malaria Control, Phnom Penh.
  • Mean V; National Center for Parasitology, Entomology and Malaria Control, Phnom Penh.
  • Kim S; Ratanakiri Provincial Health Department, Banlung.
  • Menard D; Pasteur Institute, Phnom Penh, Cambodia.
  • Grietens KP; Pasteur Institute, Phnom Penh, Cambodia.
  • Abrams S; Institute of Tropical Medicine, Antwerp.
  • Hens N; University of Antwerp, Belgium.
  • Coosemans M; University of Hasselt, Belgium.
  • Bassat Q; University of Antwerp, Belgium.
  • van Hensbroek MB; University of Hasselt, Belgium.
  • Durnez L; Institute of Tropical Medicine, Antwerp.
  • Van Bortel W; ISGlobal, Hospital Clínic-Universitat de Barcelona, Spain.
J Infect Dis ; 220(6): 1034-1043, 2019 08 09.
Article em En | MEDLINE | ID: mdl-31028393
BACKGROUND: Malaria "hotspots" have been proposed as potential intervention units for targeted malaria elimination. Little is known about hotspot formation and stability in settings outside sub-Saharan Africa. METHODS: Clustering of Plasmodium infections at the household and hotspot level was assessed over 2 years in 3 villages in eastern Cambodia. Social and spatial autocorrelation statistics were calculated to assess clustering of malaria risk, and logistic regression was used to assess the effect of living in a malaria hotspot compared to living in a malaria-positive household in the first year of the study on risk of malaria infection in the second year. RESULTS: The crude prevalence of Plasmodium infection was 8.4% in 2016 and 3.6% in 2017. Living in a hotspot in 2016 did not predict Plasmodium risk at the individual or household level in 2017 overall, but living in a Plasmodium-positive household in 2016 strongly predicted living in a Plasmodium-positive household in 2017 (Risk Ratio, 5.00 [95% confidence interval, 2.09-11.96], P < .0001). There was no consistent evidence that malaria risk clustered in groups of socially connected individuals from different households. CONCLUSIONS: Malaria risk clustered more clearly in households than in hotspots over 2 years. Household-based strategies should be prioritized in malaria elimination programs in this region.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plasmodium / Características da Família / Doenças Transmissíveis / Malária Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged / Newborn País/Região como assunto: Asia Idioma: En Ano de publicação: 2019 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Plasmodium / Características da Família / Doenças Transmissíveis / Malária Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies Limite: Adolescent / Adult / Child / Child, preschool / Female / Humans / Infant / Male / Middle aged / Newborn País/Região como assunto: Asia Idioma: En Ano de publicação: 2019 Tipo de documento: Article