Dataset Information

Malaria prevalence and incidence in an isolated, meso-endemic area of Mozambique.

ABSTRACT: Isolated areas, such as the 2 × 7 km peninsula of Linga Linga in Mozambique, are the places where malaria might be most easily eliminated. Currently available control strategies include long-lasting insecticidal bednets impregnated with pyrethroid insecticides (LLINs), rapid diagnostic tests (RDTs) for diagnosis and artemisinin based combination therapy (ACT) for treatment and these were applied on the peninsula. In 2007, following a census of the population and mapping of 500 households, five annual all-age prevalence surveys were conducted. Information on LLIN use, house construction, and animal ownership was obtained. A spatially structured generalized additive model indicated that malaria risk was greatest towards the northern end of the peninsula and that people living in houses with grass or thatch roofs had a greater risk of malaria than those living in houses with corrugated iron roofs. Incidence peaked nine weeks after rainfall (r (2) = 0.34, p = 0.0002). From 2009 incidence was measured at a centrally based project clinic. The proportion of under nine-year-old resident attendees diagnosed with malaria decreased significantly from 48% in 2009, to 35% in 2010 and 25% in 2011. At the same time, there was a shift in the peak age of cases from 1-4 year olds to 5-9 year olds. Nevertheless, in order to further reduce malaria transmission in an area such as Linga Linga, additional vector control measures need to be considered.

SUBMITTER: Charlwood JD

PROVIDER: S-EPMC4647567 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Malaria prevalence and incidence in an isolated, meso-endemic area of Mozambique.

Charlwood Jacques Derek JD Tomás Erzelia V E EV Bragança Mauro M Cuamba Nelson N Alifrangis Michael M Stanton Michelle M

PeerJ 20151105

Isolated areas, such as the 2 × 7 km peninsula of Linga Linga in Mozambique, are the places where malaria might be most easily eliminated. Currently available control strategies include long-lasting insecticidal bednets impregnated with pyrethroid insecticides (LLINs), rapid diagnostic tests (RDTs) for diagnosis and artemisinin based combination therapy (ACT) for treatment and these were applied on the peninsula. In 2007, following a census of the population and mapping of 500 households, five a ...[more]

PMID: 26587341

Similar Datasets

Project description:BackgroundAttaining the goal of reducing the global malaria burden is threatened by recent setbacks in maintaining the effectiveness of vector control interventions partly due to the emergence of pyrethroid resistant vectors. One potential strategy to address these setbacks could be combining indoor residual spraying (IRS) with non-pyrethroids and standard insecticide-treated nets (ITNs). This study aimed to provide evidence on the incremental epidemiological benefit of using third-generation IRS product in a highly endemic area with high ITN ownership.MethodsA cluster-randomized, open-label, parallel-arms, superiority trial was conducted in the Mopeia district in Zambezia, Mozambique from 2016 to 2018. The district had received mass distribution of alphacypermethrin ITNs two years before the trial and again mid-way. 86 clusters were defined, stratified and randomized to receive or not receive IRS with pirimiphos-methyl (Actellic®300 CS). Efficacy of adding IRS was assessed through malaria incidence in a cohort of children under five followed prospectively for two years, enhanced passive surveillance at health facilities and by community health workers, and yearly cross-sectional surveys at the peak of the transmission season.FindingsA total of 1536 children were enrolled in the cohort. Children in the IRS arm experienced 4,801 cases (incidence rate of 3,532 per 10,000 children-month at risk) versus 5,758 cases in the no-IRS arm (incidence rate of 4,297 per 10,000 children-month at risk), resulting in a crude risk reduction of 18% and an incidence risk ratio of 0.82 (95% CI 0.79-0.86, p-value?<?0.001). Facility and community passive surveillance showed a malaria incidence of 278 per 10,000 person-month in the IRS group (43,974 cases over 22 months) versus 358 (95% CI 355-360) per 10,000 person-month at risk in the no-IRS group (58,030 cases over 22 months), resulting in an incidence rate ratio of 0.65 (95% CI 0.60-0.71, p?<?0.001). In the 2018 survey, prevalence in children under five in the IRS arm was significantly lower than in the no-IRS arm (OR 0.54, 95% CI, 0.31-0.92, p?=?0.0241).ConclusionIn a highly endemic area with high ITN access and emerging pyrethroid resistance, adding IRS with pirimiphos-methyl resulted in significant additional protection for children under five years of age.Trial registrationClinicalTrials.gov identifier NCT02910934, registered 22 September 2016, https://clinicaltrials.gov/ct2/show/NCT02910934?term=NCT02910934&draw=2&rank=1 .

Project description:BackgroundIdentifying and targeting hyper-endemic communities within meso-endemic areas constitutes an important challenge in malaria control in endemic countries such like Angola. Recent national and global predictive maps of malaria allow the identification and quantification of the population at risk of malaria infection in Angola, but their small-scale accuracy is surrounded by large uncertainties. To observe the need to develop higher resolution malaria endemicity maps a predictive risk map of malaria infection for the municipality of Dande (a malaria endemic area in Northern Angola) was developed and compared to existing national and global maps, the role of individual, household and environmental risk factors for malaria endemicity was quantified and the spatial variation in the number of children at-risk of malaria was estimated.MethodsBayesian geostatistical models were developed to predict small-scale spatial variation using data collected during a parasitological survey conducted from May to August 2010. Maps of the posterior distributions of predicted prevalence were constructed in a geographical information system.ResultsMalaria infection was significantly associated with maternal malaria awareness, households with canvas roofing, distance to health care centre and distance to rivers. The predictive map showed remarkable spatial heterogeneity in malaria risk across the Dande municipality in contrast to previous national and global spatial risk models; large high-risk areas of malaria infection (prevalence >50%) were found in the northern and most eastern areas of the municipality, in line with the observed prevalence.ConclusionsThere is remarkable spatial heterogeneity of malaria burden which previous national and global spatial modelling studies failed to identify suggesting that the identification of malaria hot-spots within seemingly mesoendemic areas may require the generation of high resolution malaria maps. Individual, household and hydrological factors play an important role in the small-scale geographical variation of malaria risk in northern Angola. The results presented in this study can be used by provincial malaria control programme managers to help target the delivery of malaria control resources to priority areas in the Dande municipality.

Project description:BackgroundThe objective of this study is to analyze the spatial and temporal patterns of malaria incidence as to determine the means by which climatic factors such as temperature, rainfall and humidity affect its distribution in Maputo province, Mozambique.MethodsThis study presents a model of malaria that evolves in space and time in Maputo province-Mozambique, over a ten years period (1999-2008). The model incorporates malaria cases and their relation to environmental variables. Due to incompleteness of climatic data, a multiple imputation technique is employed. Additionally, the whole province is interpolated through a Gaussian process. This method overcomes the misalignment problem of environmental variables (available at meteorological stations--points) and malaria cases (available as aggregates for every district--area). Markov Chain Monte Carlo (MCMC) methods are used to obtain posterior inference and Deviance Information Criteria (DIC) to perform model comparison.ResultsA Bayesian model with interaction terms was found to be the best fitted model. Malaria incidence was associated to humidity and maximum temperature. Malaria risk increased with maximum temperature over 28 °C (relative risk (RR) of 0.0060 and 95% Bayesian credible interval (CI) of 0.00033-0.0095) and humidity (relative risk (RR) of 0.00741 and 95% Bayesian CI 0.005141-0.0093). The results would suggest that additional non-climatic factors including socio-economic status, elevation, etc. also influence malaria transmission in Mozambique.ConclusionsThese results demonstrate the potential of climate predictors particularly, humidity and maximum temperature in explaining malaria incidence risk for the studied period in Maputo province. Smoothed maps obtained as monthly average of malaria incidence allowed to visualize months of initial and peak transmission. They also illustrate a variation on malaria incidence risk that might not be related to climatic factors. However, these factors are still determinant for malaria transmission and intensity in the region.

Project description:BackgroundFollowing the 1971 ban of DDT in Bangladesh, malaria cases have increased steadily. Malaria persists as a major health problem in the thirteen south-eastern and north-eastern districts of Bangladesh. At present the national malaria control program, largely supported by the Global Fund for AIDS, Tuberculosis and Malaria (GFATM), provides interventions including advocacy at community level, Insecticide Treated Net (ITN) distribution, introduction of Rapid Diagnostic Tests (RDT) and combination therapy with Coartem. It is imperative, therefore, that baseline data on malaria prevalence and other malaria indicators are collected to assess the effectiveness of the interventions and rationalize the prevention and control efforts. The objective of this study was to obtain this baseline on the prevalence of malaria and bed net use in the thirteen malaria endemic districts of Bangladesh.Methods and principal findingsIn 2007, BRAC and ICDDR,B carried out a malaria prevalence survey in thirteen malaria endemic districts of Bangladesh. A multi-stage cluster sampling technique was used and 9750 blood samples were collected. Rapid Diagnostic Tests (RDT) were used for the diagnosis of malaria. The weighted average malaria prevalence in the thirteen endemic districts was 3.97%. In five south-eastern districts weighted average malaria prevalence rate was 6.00% and in the eight north-eastern districts weighted average malaria prevalence rate was (0.40%). The highest malaria prevalence was observed in Khagrachari district. The majority of the cases (90.18%) were P. falciparum infections. Malaria morbidity rates in five south-eastern districts was 2.94%. In eight north-eastern districts, morbidity was 0.07%.Conclusion and significanceBangladesh has hypoendemic malaria with P. falciparum the dominant parasite species. The malaria situation in the five north-eastern districts of Bangladesh in particular warrants urgent attention. Detailed maps of the baseline malaria prevalence and summaries of the data collected are provided along with the survey results in full, in a supplemental information.

Dataset Information

Malaria prevalence and incidence in an isolated, meso-endemic area of Mozambique.

Publications

Malaria prevalence and incidence in an isolated, meso-endemic area of Mozambique.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure