Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from The Gambia

Sonko, Sheriff; Jaiteh, Malanding S.; Jafali, James; Jarju, Lamin B S; D’Alessandro, Umberto; Camara, A M B; Komma-Bah, Musu; Saho, Alieu

doi:10.1186/1475-2875-13-449

Cited by 44 publications

(46 citation statements)

References 34 publications

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“…In a community level study in Malawi, children under 5 years and those between 5 and 19 years were reported to benefit equally from community bed net coverage [37]. We found another study in the Gambia that reported similar findings to our study [38]. It is possible that children <5 years were less affected than the 5-18 age group because the children are given priority by their guardians to sleep under LLINs, compared with older children.…”

Section: Discussionsupporting

confidence: 80%

Malaria Outbreak Facilitated by Appearance of Vector-Breeding Sites after Heavy Rainfall and Inadequate Preventive Measures: Nwoya District, Northern Uganda, February–May 2018

Nsereko

Kadobera

Okethwangu

et al. 2020

Journal of Environmental and Public Health

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Background. Malaria is a leading cause of morbidity and mortality in Uganda. In April 2018, malaria cases surged in Nwoya District, Northern Uganda, exceeding expected limits and thereby requiring epidemic response. We investigated this outbreak to estimate its magnitude, identify exposure factors for transmission, and recommend evidence-based control measures. Methods. We defined a malaria case as onset of fever in a resident of Anaka subcounty, Koch Goma subcounty, and Nwoya Town Council, Nwoya District, with a positive rapid diagnostic test or microscopy for malaria from 1 February to 25 May 2018. We reviewed medical records in all health facilities of affected subcounties to find cases. In a case-control study, we compared exposure factors between case-persons and asymptomatic controls matched by age and village. We also conducted entomological assessments on vector density and behavior. Results. We identified 3,879 case-persons (attack rate [AR] = 6.5%) and two deaths (case-fatality rate = 5.2/10,000). Females (AR = 8.1%) were more affected than males (AR = 4.7%) (p<0.0001). Of all age groups, 5–18 years (AR = 8.4%) were most affected. Heavy rain started in early March 2018, and a propagated outbreak followed in the first week of April 2018. In the case-control study, 55% (59/107) of case-persons and 18% (19/107) of controls had stagnant water around households for several days following rainfall (ORM-H = 5.6, 95% CI = 3.0–11); 25% (27/107) of case-persons and 51% (55/107) of controls wore full extremity covering clothes during evening hours (ORM-H = 0.30, 95% CI = 0.20–0.60); 71% (76/107) of case-persons and 85% (91/107) of controls slept under a long-lasting insecticide-treated net (LLIN) 14 days before symptom onset (ORM-H = 0.43, 95% CI = 0.22–0.85); 37% (40/107) of case-persons and 52% (56/107) of controls had access to at least one LLIN per 2 household members (ORM-H = 0.54, 95% CI = 0.30–0.97). Entomological assessment indicated active breeding sites in the entire study area; Anopheles gambiae sensu lato species were the predominant vector. Conclusion. Increased vector-breeding sites after heavy rainfall and inadequate malaria preventive measures were found to have contributed to this outbreak. We recommended increasing coverage for LLINs and larviciding breeding sites in the area.

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Section: Discussionsupporting

confidence: 80%

Malaria Outbreak Facilitated by Appearance of Vector-Breeding Sites after Heavy Rainfall and Inadequate Preventive Measures: Nwoya District, Northern Uganda, February–May 2018

Nsereko

Kadobera

Okethwangu

et al. 2020

Journal of Environmental and Public Health

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“…Temporal trends show declining malaria transmission in The Gambia and Coastal Kenya 17, 33, 34, 40 , although not in Western Kenya 41 . Asymptomatic parasite prevalence is lowest in The Gambia at 8.7% 42 , intermediate in Kilifi at 14% 43 and slightly higher in Rachuonyo South at 16% 44 .…”

Section: Methodsmentioning

confidence: 86%

Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa

Omedo¹,

Mogeni²,

Bousema³

et al. 2017

Wellcome Open Res

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The first models of malaria transmission assumed a completely Background: mixed and homogeneous population of parasites. Recent models include spatial heterogeneity and variably mixed populations. However, there are few empiric estimates of parasite mixing with which to parametize such models.: Here we genotype 276 single nucleotide polymorphisms (SNPs) in Methods 5199isolates from two Kenyan sites (Kilifi county and Rachuonyo P. falciparum South district) and one Gambian site (Kombo coastal districts) to determine the spatio-temporal extent of parasite mixing, and use Principal Component Analysis (PCA) and linear regression to examine the relationship between genetic relatedness and distance in space and time for parasite pairs.Using 107, 177 and 82 SNPs that were successfully genotyped in Results: 133, 1602, and 1034 parasite isolates from The Gambia, Kilifi and Rachuonyo South district, respectively, we show that there are no discrete geographically restricted parasite sub-populations, but instead we see a diffuse spatio-temporal structure to parasite genotypes. Genetic relatedness of sample pairs is predicted by relatedness in space and time. Discuss this article(0) Comments sample pairs is predicted by relatedness in space and time.: Our findings suggest that targeted malaria control will benefit the Conclusions surrounding community, but unfortunately also that emerging drug resistance will spread rapidly through the population.

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“…This type of house don’t offer much protection against the elements or vectors of disease unless are raised above ground [ 29 ], or its occupants use a mosquito net, but allows air flow for comfort. For example, a recent survey at the household level in The Gambia showed that children from the poorest quintiles living in houses build with poor walls, roofs and windows construction materials, were associated with a high prevalence of malaria [ 15 ], though, in the general population only poor wall housing materials were associated with a high prevalence.…”

Section: Discussionmentioning

confidence: 99%

“…Malaria has been correlated with low socio-economic development and poverty [ 10 ], and recent evidence suggests, that a causal pathway between poverty and malaria runs in both directions [ 15 ]. Furthermore, it has been pointed out that low socio-economic status (SES) doubles the risk of clinical malaria, reducing the capacity of countries to enter the elimination phase and that type of house construction is associated with increasing risk of malaria infection [ 16 - 20 ].…”

Section: Introductionmentioning

confidence: 99%

Determinants of low socio-economic status and risk of Plasmodium vivax malaria infection in Panama (2009–2012): a case–control study

Obaldía

2015

Malar J

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BackgroundIdentification of risk factors is important for the establishment of malaria elimination programmes tailored to specific regions. Type of house construction had been associated with increasing risk of acquiring malaria. This study aimed at establishing the association between determinants of low socio-economic status (SES) and type of house construction with the likelihood of living in a Plasmodium vivax malarious corregimiento (smallest political division) in Panama during 2009–2012.MethodsTo determine the association between type-2 houses (build with deciduous materials) and other determinants of low SES, with living in a malarious corregimiento, this study analyzed demographic and housing census data (2010), and malaria incidence aggregated at the corregimiento level (2009–2012), using a Spearman’s non-parametric correlation test to explore for associations, followed by a case–control study and a reduced multivariate logistic regression approach for confirmation.ResultsA descriptive temporal and spatial analysis indicated that P. vivax in Panama was associated with Amerindian reservations. Moreover, this study demonstrated that a strong correlation (deleterious effect) existed between living in a malarious corregimiento and being exposed to a type-2 house (OR = > 1.0) (p < 0.001), while, it showed an inverse correlation for exposure to type-1 houses (protective effect) (build with permanent materials) (OR = < 1.0) (p < 0.001). In the same way, a significant association between exposure to type-2 houses and the outcome of living in a malarious corregimiento was found using a case–control study approach (Chi2 test = p < 0.001), that was confirmed applying a reduced multivariate logistic regression fitted model.ConclusionsThis study demonstrated that living in a P. vivax malarious corregimiento in Panama during 2009–2012 was strongly correlated with those corregimientos having a high proportion of type-2 houses. A multivariate logistic regression approach at the house and corregimiento level indicated a strong association of type-2 houses, dirt floors and illiteracy with the likelihood of living in a malarious corregimiento. It is expected that these findings will help implement a multi-sectorial approach for the elimination of malaria in poor areas of Panama where malaria is endemic, which emphasizes house improvements such as mosquito-proofing and socio-economic development.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-014-0529-7) contains supplementary material, which is available to authorized users.

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Does socio-economic status explain the differentials in malaria parasite prevalence? Evidence from The Gambia

Cited by 44 publications

References 34 publications

Malaria Outbreak Facilitated by Appearance of Vector-Breeding Sites after Heavy Rainfall and Inadequate Preventive Measures: Nwoya District, Northern Uganda, February–May 2018

Malaria Outbreak Facilitated by Appearance of Vector-Breeding Sites after Heavy Rainfall and Inadequate Preventive Measures: Nwoya District, Northern Uganda, February–May 2018

Micro-epidemiological structuring of Plasmodium falciparum parasite populations in regions with varying transmission intensities in Africa

Determinants of low socio-economic status and risk of Plasmodium vivax malaria infection in Panama (2009–2012): a case–control study

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