Dataset Information

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012.

ABSTRACT:

Background

In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal and to identify the meteorological, environmental, and preventive factors that influence this variation.

Methods

This study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 575 villages of central Senegal (total population approximately 500,000) as part of a trial of seasonal malaria chemoprevention (SMC). Data on weekly rainfall and annual vegetation types were obtained for each village through remote sensing. The time series of weekly malaria incidence for the entire study area was divided into periods of high and low transmission using change-point analysis. Malaria hotspots were detected during each transmission period with the SaTScan method. The effects of rainfall, vegetation type, and SMC intervention on the spatio-temporal variation of malaria hotspots were assessed using a General Additive Mixed Model.

Results

The malaria incidence for the entire area varied between 0 and 115.34 cases/100,000 person weeks during the study period. During high transmission periods, the cumulative malaria incidence rate varied between 7.53 and 38.1 cases/100,000 person-weeks, and the number of hotspot villages varied between 62 and 147. During low transmission periods, the cumulative malaria incidence rate varied between 0.83 and 2.73 cases/100,000 person-weeks, and the number of hotspot villages varied between 10 and 43. Villages with SMC were less likely to be hotspots (OR?=?0.48, IC95%: 0.33-0.68). The association between rainfall and hotspot status was non-linear and depended on both vegetation type and amount of rainfall. The association between village location in the study area and hotspot status was also shown.

Conclusion

In our study, malaria hotspots varied over space and time according to a combination of meteorological, environmental, and preventive factors. By taking into consideration the environmental and meteorological characteristics common to all hotspots, monitoring of these factors could lead targeted public health interventions at the local level. Moreover, spatial hotspots and foci of malaria persisting during LTPs need to be further addressed.

Trial registration

The data used in this work were obtained from a clinical trial registered on July 10, 2008 at www.clinicaltrials.gov under NCT00712374.

SUBMITTER: Dieng S

PROVIDER: S-EPMC7301493 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012.

Dieng Sokhna S Ba El Hadj EH Cissé Badara B Sallah Kankoe K Guindo Abdoulaye A Ouedraogo Boukary B Piarroux Martine M Rebaudet Stanislas S Piarroux Renaud R Landier Jordi J Sokhna Cheikh C Gaudart Jean J

BMC infectious diseases 20200617 1

<h4>Background</h4>In malaria endemic areas, identifying spatio-temporal hotspots is becoming an important element of innovative control strategies targeting transmission bottlenecks. The aim of this work was to describe the spatio-temporal variation of malaria hotspots in central Senegal and to identify the meteorological, environmental, and preventive factors that influence this variation.<h4>Methods</h4>This study analysed the weekly incidence of malaria cases recorded from 2008 to 2012 in 57 ...[more]

PMID: 32552759

Similar Datasets

Project description:BackgroundIn view of ongoing pandemic threats such as the recent human cases of novel avian influenza A(H7N9) in China, it is important that all countries continue their preparedness efforts. Since 2006, Central American countries have received donor funding and technical assistance from the U.S. Centers for Disease Control and Prevention (CDC) to build and improve their capacity for influenza surveillance and pandemic preparedness. Our objective was to measure changes in pandemic preparedness in this region, and explore factors associated with these changes, using evaluations conducted between 2008 and 2012.MethodsEight Central American countries scored their pandemic preparedness across 12 capabilities in 2008, 2010 and 2012, using a standardized tool developed by CDC. Scores were calculated by country and capability and compared between evaluation years using the Student's t-test and Wilcoxon Rank Sum test, respectively. Virological data reported to WHO were used to assess changes in testing capacity between evaluation years. Linear regression was used to examine associations between scores, donor funding, technical assistance and WHO reporting.ResultsAll countries improved their pandemic preparedness between 2008 and 2012 and seven made statistically significant gains (p?<?0.05). Increases in median scores were observed for all 12 capabilities over the same period and were statistically significant for eight of these (p?<?0.05): country planning, communications, routine influenza surveillance, national respiratory disease surveillance, outbreak response, resources for containment, community interventions and health sector response. We found a positive association between preparedness scores and cumulative funding between 2006 and 2011 (R2?=?0.5, p?<?0.01). The number of specimens reported to WHO from participating countries increased significantly from 5,551 (2008) to 18,172 (2012) (p?<?0.01).ConclusionsCentral America has made significant improvements in influenza pandemic preparedness between 2008 and 2012. U.S. donor funding and technical assistance provided to the region is likely to have contributed to the improvements we observed, although information on other sources of funding and support was unavailable to study. Gains are also likely the result of countries' response to the 2009 influenza pandemic. Further research is required to determine the degree to which pandemic improvements are sustainable.

Project description:BackgroundEffective reduction of tuberculosis (TB) requires information on the distribution of TB incidence rate across time and location. This study aims to identify the spatio-temporal pattern of TB incidence rate in Iran between 2008 and 2018.MethodsThis cross-sectional study was conducted on aggregated TB data (50,500 patients) at the provincial level provided by the Ministry of Health in Iran between 2008 and 2018. The Anselin Local Moran's I and Getis-Ord Gi* were performed to identify the spatial variations of the disease. Furthermore, spatial scan statistic was employed for purely temporal and spatio-temporal analyses. In all instances, the null hypothesis of no clusters was rejected at p ≤ 0.05.ResultsThe overall incidence rate of TB decreased from 13.46 per 100,000 (95% CI: 13.19-13.73) in 2008 to 10.88 per 100,000 (95% CI: 10.65-11.11) in 2018. The highest incidence rate of TB was observed in southeast and northeast of Iran for the whole study period. Additionally, spatial cluster analysis discovered Khuzestan Province, in the West of the country, having significantly higher rates than neighbouring provinces in terms of both total TB and smear-positive pulmonary TB (SPPTB). Purely temporal analysis showed that high-rate and low-rate clusters were predominantly distributed in the time periods 2010-2014 and 2017-2018. Spatio-temporal results showed that the statistically significant clusters were mainly distributed from centre to the east during the study period. Some high-trend TB and SPPTB statistically significant clusters were found.ConclusionThe results provided an overview of the latest TB spatio-temporal status In Iran and identified decreasing trends of TB in the 2008-2018 period. Despite the decreasing incidence rate, there is still need for screening, and targeting of preventive interventions, especially in high-risk areas. Knowledge of the spatio-temporal pattern of TB can be useful for policy development as the information regarding the high-risk areas would contribute to the selection of areas needed to be targeted for the expansion of health facilities.

Project description:Despite its high ecological importance, the commensal interactions at community level are poorly studied. In tropical dry forests (TDF) there is a great diversity of species adapted to the high seasonality that characterizes them; however, little is known regarding how the spatial and temporal availability of resources generates changes in the pattern of commensal interactions. We experimentally studied changes in the diversity, composition, and pattern of interactions in spatio-temporal associations between the saproxylophagous beetles and their host trees in a TDF in Morelos, Mexico. A total of 65 host tree species were selected, from which 16 wood sections were obtained per species. These sections were exposed in the field to allow oviposition by the cerambycids under four different (spatio-temporal) treatments. We analyzed the network structure and generated indices at species level (i.e., specialization, species strength, and effective partners) and those related to physical characteristics of the wood (hardness and degradation rate) and the cerambycids (body size). In total, 1,323 individuals of 57 species of cerambycids emerged. Our results showed that, independently of the space and time, the network presented a nested and modular structure, with a high specialization degree and a high turnover of cerambycid species and their interactions. In general, we found that the cerambycids are mostly associated with softwood species with a lower decomposition rate of wood, as well as with the most abundant host species. The commensalistic interactions between the cerambycids and their host trees are highly specialized but are not spatio-temporally static. The high turnover in the interactions is caused by the emergence patterns of cerambycids, which seem to restrict their use to certain species. The knowledge of the spatio-temporal variation in Cerambycidae-host tree interactions allows us to predict how environmental and structural changes in the habitat can modify the species ensemble, and therefore its interactions.

Dataset Information

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012.

Background

Methods

Results

Conclusion

Trial registration

Publications

Spatio-temporal variation of malaria hotspots in Central Senegal, 2008-2012.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets