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Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso.

ABSTRACT: Control of malaria in pregnancy (MiP) remains a major challenge in Burkina Faso. Surveillance of the burden due to MiP based on routinely collected data at a fine-scale level, followed by an appropriate analysis and interpretation, may be crucial for evaluating and improving the effectiveness of existing control measures. We described the spatio-temporal dynamics of MiP at the community-level and assessed health program effects, mainly community-based health promotion, results-based financing, and intermittent-preventive-treatment with sulphadoxine-pyrimethamine (IPTp-SP). Community-aggregated monthly MiP cases were downloaded from Health Management Information System and combined with covariates from other sources. The MiP spatio-temporal pattern was decomposed into three components: overall spatial and temporal trends and space-time interaction. Bayesian hierarchical spatio-temporal Poisson models were used to fit the MiP incidence rate and assess health program effects. The overall annual incidence increased between 2015 and 2017. The findings reveal spatio-temporal heterogenicity throughout the year, which peaked during rainy season. From the model without covariates, 96 communities located mainly in the Cascades, South-West, Center-West, Center-East, and Eastern regions, exhibited significant relative-risk levels. The combined effect (significant reducing effect) of RBF, health promotion and IPTp-SP strategies was greatest in 17.7% (17/96) of high burden malaria communities. Despite intensification of control efforts, MiP remains high at the community-scale. The provided risk maps are useful tools for highlighting areas where interventions should be optimized, particularly in high-risk communities.

SUBMITTER: Rouamba T

PROVIDER: S-EPMC7021681 | biostudies-literature | 2020 Feb

REPOSITORIES: biostudies-literature

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Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso.

Rouamba Toussaint T Samadoulougou Sekou S Tinto Halidou H Alegana Victor A VA Kirakoya-Samadoulougou Fati F

Scientific reports 20200214 1

Control of malaria in pregnancy (MiP) remains a major challenge in Burkina Faso. Surveillance of the burden due to MiP based on routinely collected data at a fine-scale level, followed by an appropriate analysis and interpretation, may be crucial for evaluating and improving the effectiveness of existing control measures. We described the spatio-temporal dynamics of MiP at the community-level and assessed health program effects, mainly community-based health promotion, results-based financing, a ...[more]

PMID: 32060297

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Project description:BackgroundThe number of malaria cases worldwide has increased, with over 241 million cases and 69,000 more deaths in 2020 compared to 2019. Burkina Faso recorded over 11 million malaria cases in 2020, resulting in nearly 4,000 deaths. The overall incidence of malaria in Burkina Faso has been steadily increasing since 2016. This study investigates the spatiotemporal pattern and environmental and meteorological determinants of malaria incidence in Burkina Faso.MethodsWe described the temporal dynamics of malaria cases by detecting the transmission periods and the evolution trend from 2013 to 2018. We detected hotspots using spatial scan statistics. We assessed different environmental zones through a hierarchical clustering and analyzed the environmental and climatic data to identify their association with malaria incidence at the national and at the district's levels through generalized additive models. We also assessed the time lag between malaria peaks onset and the rainfall at the district level. The environmental and climatic data were synthetized into indicators.ResultsThe study found that malaria incidence had a seasonal pattern, with high transmission occurring during the rainy seasons. We also found an increasing trend in the incidence. The highest-risk districts for malaria incidence were identified, with a significant expansion of high-risk areas from less than half of the districts in 2013-2014 to nearly 90% of the districts in 2017-2018. We identified three classes of health districts based on environmental and climatic data, with the northern, south-western, and western districts forming separate clusters. Additionally, we found that the time lag between malaria peaks onset and the rainfall at the district level varied from 7 weeks to 17 weeks with a median at 10 weeks. Environmental and climatic factors have been found to be associated with the number of cases both at global and districts levels.ConclusionThe study provides important insights into the environmental and spatiotemporal patterns of malaria in Burkina Faso by assessing the spatio temporal dynamics of Malaria cases but also linking those dynamics to the environmental and climatic factors. The findings highlight the importance of targeted control strategies to reduce the burden of malaria in high-risk areas as we found that Malaria epidemiology is complex and linked to many factors that make some regions more at risk than others.

Project description:Reducing the 2015 level of malaria mortality by 90% by 2030 is a goal set by the World Health Organization (WHO). In Burkina Faso, several malaria control programs proven to be effective were implemented over the last decade. In parallel, the progressive strengthening of the health surveillance system is generating valuable data, which represents a great opportunity for analyzing the trends in malaria burden and assessing the effect of these control programs. Complementary programs were rolled out at different time points and paces, and the present work aims at investigating both the spatial and temporal pattern of malaria case fatality rate (mCFR) by considering the effect of combining specific and unspecific malaria control programs. To this end, data on severe malaria cases and malaria deaths, aggregated at health district level between January 2013 and December 2018, were extracted from the national health data repository (ENDOS-BF). A Bayesian spatiotemporal zero-inflated Poisson model was fitted to quantify the strength of the association of malaria control programs with monthly mCFR trends at health district level. The model was adjusted for contextual variables. We found that monthly mCFR decreased from 2.0 (95% IC 1.9-2.1%) to 0.9 (95% IC 0.8-1.0%) deaths for 100 severe malaria cases in 2013 and 2018, respectively. Health districts with high mCFR were identified in the northern, northwestern and southwestern parts of the country. The availability of malaria rapid diagnosis tests (IRR: 0.54; CrI: 0.47, 0.62) and treatment (IRR: 0.50; CrI: 0.41, 0.61) were significantly associated with a reduction in the mCFR. The risk of dying from malaria was lower in the period after the free healthcare policy compared with the period before (IRR: 0.47; CrI: 0.38, 0.58). Our findings highlighted locations that are most in need of targeted interventions and the necessity to sustain and strengthen the launched health programs to further reduce the malaria deaths in Burkina Faso.

Project description:Malaria is a parasitic disease, endemic in many tropical and sub-tropical countries. Malaria is a well-known disease, familiar to almost all people in endemic regions, as they or their family are regularly confronted with it; everyone in these regions has probably experienced the disease, at least once in their life. To investigate the social perceptions of malaria in Burkina Faso, including its diagnosis-driven treatment, we have conducted a survey in both urban (Saint Camille Hospital, Ouagadougou HOSCO) and rural (Boussé Hospital) areas. Fifty-six individuals, mostly representatives of the society variability, were surveyed by questionnaires and 2 focus groups were organized with traditional healers. In general, populations seem to have grasped the causes, symptoms and means of preventing the disease. However, the majority of interviewees make a marked confusion between malaria and dengue; dengue fever is considered like a severe form of malaria. The care modalities (modern and/or traditional medicine) are plural and the choice of therapeutic practice depends on both the socio-economic conditions and education level of the patient. Whereas some patients mark preferences for one type of medicine, others simultaneously recourse to both; for these, a medicine does not outperform the other and their combination multiplies the chances of a quick recovery. Whether for modern or traditional medicine, the diagnosis is considered very important for effective disease management. Modern medicine uses diagnostic tools based on light microscopy and immunochromatography (rapid diagnostic tests; RDT); traditional medicine has its own diagnostic logic but nevertheless recognizes modern medicine diagnosis to guide its therapy. 90 % of those interviewed first use modern medicine to seek an accurate diagnosis of their disease and thus to receive adequate treatment. Presumptive treatments are still widely prescribed and accepted by most patients who trust the judgment of their caregiver, not perceiving any benefit to an objective diagnosis. In front of a negative diagnosis, patient reactions are diverse, some accepting investigations for other diseases (45 %), others opting for self-medication (15 %), others resorting to traditional medicine (20 %). All are unanimous in the importance of diagnosis and are in favor of in-development diagnostic technologies, provided these obviously meet the features of reliability, ease of use, availability and, of course, economical accessibility.

Project description:BACKGROUND:Infants are thought to be protected against malaria during the first months of life mainly due to passage of maternal antibodies. However, in high transmission settings, malaria in early infancy is not uncommon and susceptibility to the infections varies between individuals. This study aimed to determine malaria morbidity and infection during early childhood in rural Burkina Faso. METHODS:Malariometric indices were determined over 1-year follow-up in a birth cohort of 734 infants living in Nanoro health district. Clinical malaria episodes were determined by passive case detection at peripheral health centres while asymptomatic malaria infections were identified during 4 cross-sectional surveys at 3, 6, 9 and 12 months of age. Plasmodium falciparum infections were detected by rapid diagnostic test and/or light microscopy (LM) and quantitative PCR (qPCR). RESULTS:In total, 717 clinical episodes were diagnosed by qPCR over 8335.18 person-months at risk. The overall malaria incidence was 1.03 per child-year and increased from 0.27 per child-year at 0-3 months of age to 1.92 per child-year at 9-12 months of age. Some 59% of children experienced at least one clinical episode with a median survival time estimated at 9.9 months, while 20% of infants experienced the first episode before 6 months of age. The majority of the clinical episodes were attributable to microscopic parasitaemia (84.2%), and there was a positive correlation between parasite density and age (Spearman's rho = 0.30; P < 0.0001). Prevalence of asymptomatic infections was similar at 3, 6 and 9 months of age (17.7-20.1%) and nearly 1.6 times higher at 12 months (31.3%). Importantly, gametocyte prevalence among the LM-positive study population was 6.7%, but increased to 10% among asymptomatic infections. In addition, 46% of asymptomatic infections were only detected by qPCR suggesting that infants below 1 year are a potential reservoir for sustaining malaria transmission. Both symptomatic and asymptomatic infections showed marked seasonal distribution with the highest transmission period (July to December) accounting for about 89 and 77% of those infections, respectively. CONCLUSIONS:These findings indicate high and marked age and seasonal-dependency of malaria infections and disease during the first year of life in Nanoro, calling for intensified efforts to control malaria in rural Burkina Faso.

Dataset Information

Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso.

Publications

Bayesian Spatiotemporal Modeling of Routinely Collected Data to Assess the Effect of Health Programs in Malaria Incidence During Pregnancy in Burkina Faso.

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