Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana.
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ABSTRACT:
SUBMITTER: Amratia P
PROVIDER: S-EPMC6420752 | biostudies-literature | 2019 Mar
REPOSITORIES: biostudies-literature
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Characterizing local-scale heterogeneity of malaria risk: a case study in Bunkpurugu-Yunyoo district in northern Ghana.
Amratia Punam P Psychas Paul P Abuaku Benjamin B Ahorlu Collins C Millar Justin J Oppong Samuel S Koram Kwadwo K Valle Denis D
Malaria journal 20190315 1
<h4>Background</h4>Bayesian methods have been used to generate country-level and global maps of malaria prevalence. With increasing availability of detailed malaria surveillance data, these methodologies can also be used to identify fine-scale heterogeneity of malaria parasitaemia for operational prevention and control of malaria.<h4>Methods</h4>In this article, a Bayesian geostatistical model was applied to six malaria parasitaemia surveys conducted during rainy and dry seasons between November ...[more]
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Project description:BackgroundGlobally in 2015 about 214 million malaria cases and 438,000 deaths were reported with 75% were from Sub-Saharan Africa. Malaria transmission in Ethiopia is unstable, and outbreaks are considered public health emergencies. Understanding the trigger for outbreaks in low-transmission areas can help facilitate malaria elimination. On July 8th malaria outbreak was reported from Laelay Adyabo district. The objective was to investigate the magnitude and associated factors with malaria outbreak.MethodsWe defined a case as confirmed malaria using microscopy or a rapid diagnostic test for Plasmodium parasites in a resident of Laelay-Adyabo District from July 9-28, 2017. We identified cases by reviewing health facility records and conducted a case-control study using randomly-selected cases from a line list, and two neighborhood controls per case. A pretested semi-structured questionnaire adapted from WHO malaria guidelines was used to collect data from case-patients and controls. We calculated crude (COR) and adjusted (AOR) odds ratios to identify factors associated with malaria.ResultA total of 145 confirmed malaria cases (57.9% males) were identified with village attack rate (AR) of 12.1/1000. The AR was higher among males than females (14.1 verses 10.1/1000), children aged 5-14 years (12.9/1000), and in Zelazle Kebelle (13.6/1000 population). Wearing protective clothing (AOR = 0.27, 95% CI 0.11-0.66), having good knowledge of malaria transmission (AOR = 0.25, 95% CI 0.08-0.75), having waste collection material at home (AOR = 0.25 95% CI 0.11-0.61), availability of mosquito breeding sites around home (AOR = 9.08, 95% CI 3.6-22.93), and staying outdoor overnight (AOR = 3.7, 95% CI 1.44-9.56) were independently associated with malaria.ConclusionThe overall attack rate for malaria during this outbreak was high affecting > 1% of the population. Wearing protective clothing at night, knowing about malaria transmission, having mosquito breeding sites around the home, staying outdoors overnight, and having waste collection material in their house were predictors of the infection. Laelay Adyabo district health office should provide health education on malaria transmission and prevention measures and how to clear mosquito breeding sites.
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Project description:BackgroundVector bionomics are important aspects of vector-borne disease control programs. Mosquito-biting risks are affected by environmental, mosquito behavior and human factors, which are important for assessing exposure risk and intervention impacts. This study estimated malaria transmission risk based on vector-human interactions in northern Ghana, where indoor residual spraying (IRS) and insecticide-treated nets (ITNs) have been deployed.MethodsIndoor and outdoor human biting rates (HBRs) were measured using monthly human landing catches (HLCs) from June 2017 to April 2019. Mosquitoes collected were identified to species level, and Anopheles gambiae sensu lato (An. gambiae s.l.) samples were examined for parity and infectivity. The HBRs were adjusted using mosquito parity and human behavioral observations.ResultsAnopheles gambiae was the main vector species in the IRS (81%) and control (83%) communities. Indoor and outdoor HBRs were similar in both the IRS intervention (10.6 vs. 11.3 bites per person per night [b/p/n]; z = -0.33, P = 0.745) and control communities (18.8 vs. 16.4 b/p/n; z = 1.57, P = 0.115). The mean proportion of parous An. gambiae s.l. was lower in IRS communities (44.6%) than in control communities (71.7%). After adjusting for human behavior observations and parity, the combined effect of IRS and ITN utilization (IRS: 37.8%; control: 57.3%) on reducing malaria transmission risk was 58% in IRS + ITN communities and 27% in control communities with ITNs alone (z = -4.07, P < 0.001). However, this also revealed that about 41% and 31% of outdoor adjusted bites in IRS and control communities respectively, occurred before bed time (10:00 pm). The mean directly measured annual entomologic inoculation rates (EIRs) during the study were 6.1 infective bites per person per year (ib/p/yr) for IRS communities and 16.3 ib/p/yr for control communities. After considering vector survival and observed human behavior, the estimated EIR for IRS communities was 1.8 ib/p/yr, which represents about a 70% overestimation of risk compared to the directly measured EIR; for control communities, it was 13.6 ib/p/yr (16% overestimation).ConclusionIndoor residual spraying significantly impacted entomological indicators of malaria transmission. The results of this study indicate that vector bionomics alone do not provide an accurate assessment of malaria transmission exposure risk. By accounting for human behavior parameters, we found that high coverage of ITNs alone had less impact on malaria transmission indices than combining ITNs with IRS, likely due to observed low net use. Reinforcing effective communication for behavioral change in net use and IRS could further reduce malaria transmission.
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Project description:A comprehensive chemical quality assessment of groundwater resources in the Talensi District has been conducted using conventional graphical methods and multivariate statistical techniques. The study sought to determine the main controls of groundwater chemistry and its suitability for domestic and irrigation purposes in the district. Silicate and carbonate mineral weathering were identified as the main controls on groundwater chemistry in the district, with reverse ion exchange also playing a role. High nitrate and lead levels observed have been associated with agrochemicals and wastewater from farms and homes. Three main flow regimes have been identified with Q-mode cluster analysis, in which mixed cation water types have been revealed, where areas designated as recharge zones are dominated by Na+?+?K+-Mg2+-HCO3 - fresh water types characterised by low mineralisation and pH, which evolve into Mg2+- Na+?+?K+- HCO3 - fresh water type with corresponding increased mineralisation of the groundwater. Based on the water quality index (WQI) technique modified for the district and an interpolation technique using ordinary kriging developed from a well-fitted exponential semivariogram for the estimated WQIs, the groundwater quality has been spatially classified as generally 'good' to 'excellent' for domestic purposes. Generally, the quality of groundwater for domestic usage deteriorates as one moves towards the north of the district, whereas waters in the east and west present the best quality. Classifications based on the United States Salinity Laboratory (USSL), Wilcox, and Doneen diagrams suggest that groundwater from the unconfined aquifers of the district is of excellent quality for irrigation purposes.
| S-EPMC7171681 | biostudies-literature
Project description:In areas of low and unstable transmission, malaria cases occur in populations with lower access to malaria services and interventions, and in groups with specific malaria risk exposures often away from the household. In support of the Namibian National Vector Borne Disease Program's drive to better target interventions based upon risk, we implemented a health facility-based case control study aimed to identify risk factors for symptomatic malaria in Zambezi Region, northern Namibia. A total of 770 febrile individuals reporting to 6 health facilities and testing positive by rapid diagnostic test (RDT) between February 2015 and April 2016 were recruited as cases; 641 febrile individuals testing negative by RDT at the same health facilities through June 2016 were recruited as controls. Data on socio-demographics, housing construction, overnight travel, use of malaria prevention and outdoor behaviors at night were collected through interview and recorded on a tablet-based questionnaire. Remotely-sensed environmental data were extracted for geo-located village residence locations. Multivariable logistic regression was conducted to identify risk factors and latent class analyses (LCA) used to identify and characterize high-risk subgroups. The majority of participants (87% of cases and 69% of controls) were recruited during the 2016 transmission season, an outbreak year in Southern Africa. After adjustment, cases were more likely to be cattle herders (Adjusted Odds Ratio (aOR): 4.46 95%CI 1.05-18.96), members of the police or other security personnel (aOR: 4.60 95%CI: 1.16-18.16), and pensioners/unemployed persons (aOR: 2.25 95%CI 1.24-4.08), compared to agricultural workers (most common category). Children (aOR 2.28 95%CI 1.13-4.59) and self-identified students were at higher risk of malaria (aOR: 4.32 95%CI 2.31-8.10). Other actionable risk factors for malaria included housing and behavioral characteristics, including traditional home construction and sleeping in an open structure (versus modern structure: aOR: 2.01 95%CI 1.45-2.79 and aOR: 4.76 95%CI: 2.14-10.57); cross border travel in the prior 30 days (aOR: 10.55 95%CI 2.94-37.84); and outdoor agricultural work at night (aOR: 2.09 95%CI 1.12-3.87). Malaria preventive activities were all protective and included personal use of an insecticide treated net (ITN) (aOR: 0.61 95%CI 0.42-0.87), adequate household ITN coverage (aOR: 0.63 95%CI 0.42-0.94), and household indoor residual spraying (IRS) in the past year (versus never sprayed: (aOR: 0.63 95%CI 0.44-0.90). A number of environmental factors were associated with increased risk of malaria, including lower temperatures, higher rainfall and increased vegetation for the 30 days prior to diagnosis and residing more than 5 minutes from a health facility. LCA identified six classes of cases, with class membership strongly correlated with occupation, age and select behavioral risk factors. Use of ITNs and IRS coverage was similarly low across classes. For malaria elimination these high-risk groups will need targeted and tailored intervention strategies, for example, by implementing alternative delivery methods of interventions through schools and worksites, as well as the use of specific interventions that address outdoor transmission.
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Project description:This study was conducted to quantify the levels and measure the health risk of selected heavy metals (Fe, Zn, Pb, Mn, Cr, Ni) in milled millet and maize from 10 communities in the Tolon District, northern region of Ghana. Control samples of maize and millet were also prepared in order to identify whether the sources of the heavy metals were limited to the milling process or otherwise. The heavy metals present in the collected milled samples were quantified using an AAS Varian Spectra 220 FS. The average concentrations of the selected heavy metals in the milled maize samples were the following: Fe = 1.3392 ± 0.4341 mg/kg, Ni = 0.9502 ± 0.2696 mg/kg, Pb = 2.2177 ± 0.0534 mg/kg, Cr = 0.4359 ± 0.3574 mg/kg, Zn = 0.6809 ± 0.0534 mg/kg, and Mn = 0.3550 ± 0.1042 mg/kg. Milled millet samples recorded mean concentration of the heavy metals as Fe = 1.9467 ± 1.0597 mg/kg, Ni = 0.9520 ± 0.1218 mg/kg, Pb = 2.2780 ± 0.0221 mg/kg, Cr = 0.3421 ± 0.1498 mg/kg, Zn = 0.8540 ± 0.1139 mg/kg, and Mn = 0.4241 ± 0.0859 mg/kg. All selected heavy metals concentrations were below standards in food except Pb. Locally made mill plates were found to leach heavy metals in the milled flours due to the direct contact of the grains with the mill plates. However, the comparison of milled to pounded flour (control samples) indicated other potential sources of heavy metals aside from the disk attrition mill. The health risk assessment revealed no potential hazards nor cancer risk in both children and adults.
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Project description:BACKGROUND: The relationship between entomological measures of malaria transmission intensity and mortality remains uncertain. This is partly because transmission is heterogeneous even within small geographical areas. Studying this relationship requires high resolution, spatially structured, longitudinal entomological data. Geostatistical models that have been used to analyse the spatio-temporal heterogeneity have not considered the uncertainty in both sporozoite rate (SR) and mosquito density data. This study analysed data from Kassena-Nankana districts in northern Ghana to obtain small area estimates of malaria transmission rates allowing for this uncertainty. METHODS: Independent Bayesian geostatistical models for sporozoite rate and mosquito density were fitted to produce explicit entomological inoculation rate (EIR) estimates for small areas and short time periods, controlling for environmental factors. RESULTS: Mosquitoes were trapped from 2,803 unique locations for three years using mainly CDC light traps. Anopheles gambiae constituted 52%, the rest were Anopheles funestus. Mean biting rates for An. funestus and An. gambiae were 32 and 33 respectively. Most bites occurred in September, the wettest month. The sporozoite rates were higher in the dry periods of the last two years compared with the wet period. The annual EIR varied from 1,132 to 157 infective bites. Monthly EIR varied between zero and 388 infective bites. Spatial correlation for SR was lower than that of mosquito densities. CONCLUSION: This study confirms the presence of spatio-temporal heterogeneity in malaria transmission within a small geographical area. Spatial variance was stronger than temporal especially in the SR. The estimated EIR will be used in mortality analysis for the area.
| S-EPMC3618087 | biostudies-other
Project description:BackgroundMapping malaria risk is an integral component of efficient resource allocation. Routine health facility data are convenient to collect, but without information on the locations at which transmission occurred, their utility for predicting variation in risk at a sub-catchment level is presently unclear.MethodsUsing routinely collected health facility level case data in Swaziland between 2011-2013, and fine scale environmental and ecological variables, this study explores the use of a hierarchical Bayesian modelling framework for downscaling risk maps from health facility catchment level to a fine scale (1 km x 1 km). Fine scale predictions were validated using known household locations of cases and a random sample of points to act as pseudo-controls.ResultsResults show that fine-scale predictions were able to discriminate between cases and pseudo-controls with an AUC value of 0.84. When scaled up to catchment level, predicted numbers of cases per health facility showed broad correspondence with observed numbers of cases with little bias, with 84 of the 101 health facilities with zero cases correctly predicted as having zero cases.ConclusionsThis method holds promise for helping countries in pre-elimination and elimination stages use health facility level data to produce accurate risk maps at finer scales. Further validation in other transmission settings and an evaluation of the operational value of the approach is necessary.
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2017-03-08 | GSE84604 | GEO