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Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin.

ABSTRACT: Despite the recent malaria burden reduction in the Americas, focal transmission persists across the Amazon Basin. Timely analysis of surveillance data is crucial to characterize high-risk individuals and households for better targeting of regional elimination efforts. Here we analyzed 5,480 records of laboratory-confirmed clinical malaria episodes combined with demographic and socioeconomic information to identify risk factors for elevated malaria incidence in Mâncio Lima, the main urban transmission hotspot of Brazil. Overdispersed malaria count data clustered into households were fitted with random-effects zero-inflated negative binomial regression models. Random-effect predictors were used to characterize the spatial heterogeneity in malaria risk at the household level. Adult males were identified as the population stratum at greatest risk, likely due to increased occupational exposure away of the town. However, poor housing and residence in the less urbanized periphery of the town were also found to be key predictors of malaria risk, consistent with a substantial local transmission. Two thirds of the 8,878 urban residents remained uninfected after 23,975 person-years of follow-up. Importantly, we estimated that nearly 14% of them, mostly children and older adults living in the central urban hub, were free of malaria risk, being either unexposed, naturally unsusceptible, or immune to infection. We conclude that statistical modeling of routinely collected, but often neglected, malaria surveillance data can be explored to characterize drivers of transmission heterogeneity at the community level and provide evidence for the rational deployment of control interventions.

SUBMITTER: Corder RM

PROVIDER: S-EPMC6688813 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundStudies in South-East Asia have suggested that early diagnosis and treatment with artesunate (AS) and mefloquine (MQ) combination therapy may reduce the transmission of Plasmodium falciparum malaria and the progression of MQ resistance.MethodsThe effectiveness of a fixed-dose combination of AS and MQ (ASMQ) in reducing malaria transmission was tested in isolated communities of the Juruá valley in the Amazon region.Priority municipalities within the Brazilian Legal Amazon area were selected according to pre-specified criteria. Routine national malaria control programmatic procedures were followed. Existing health structures were reinforced and health care workers were trained to treat with ASMQ all confirmed falciparum malaria cases that match inclusion criteria. A local pharmacovigilance structure was implemented. Incidence of malaria and hospitalizations were recorded two years before, during, and after the fixed-dose ASMQ intervention. In total, between July 2006 and December 2008, 23,845 patients received ASMQ. Two statistical modelling approaches were applied to monthly time series of P. falciparum malaria incidence rates, P. falciparum/Plasmodium vivax infection ratio, and malaria hospital admissions rates. All the time series ranged from January 2004 to December 2008, whilst the intervention period span from July 2006 to December 2008.ResultsThe ASMQ intervention had a highly significant impact on the mean level of each time series, adjusted for trend and season, of 0.34 (95% CI 0.20 - 0.58) for the P. falciparum malaria incidence rates, 0.67 (95% CI 0.50 - 0.89) for the P. falciparum/P. vivax infection ratio, and 0.53 (95% CI 0.41 - 0.69) for the hospital admission rates. There was also a significant change in the seasonal (or monthly) pattern of the time series before and after intervention, with the elimination of the malaria seasonal peak in the rainy months of the years following the introduction of ASMQ. No serious adverse events relating to the use of fixed-dose ASMQ were reported.ConclusionsIn the remote region of the Juruá valley, the early detection of malaria by health care workers and treatment with fixed-dose ASMQ was feasible and efficacious, and significantly reduced the incidence and morbidity of P. falciparum malaria.

Project description:Molecular surveillance for malaria has great potential to support national malaria control programs (NMCPs). To bridge the gap between research and implementation, several applications (use cases) have been identified to align research, technology development, and public health efforts. For implementation at NMCPs, there is an urgent need for feasible and cost-effective tools. We designed a new highly multiplexed deep sequencing assay (Pf AmpliSeq), which is compatible with benchtop sequencers, that allows high-accuracy sequencing with higher coverage and lower cost than whole-genome sequencing (WGS), targeting genomic regions of interest. The novelty of the assay is its high number of targets multiplexed into one easy workflow, combining population genetic markers with 13 nearly full-length resistance genes, which is applicable for many different use cases. We provide the first proof of principle for hrp2 and hrp3 deletion detection using amplicon sequencing. Initial sequence data processing can be performed automatically, and subsequent variant analysis requires minimal bioinformatic skills using any tabulated data analysis program. The assay was validated using a retrospective sample collection (n = 254) from the Peruvian Amazon between 2003 and 2018. By combining phenotypic markers and a within-country 28-single-nucleotide-polymorphism (SNP) barcode, we were able to distinguish different lineages with multiple resistance haplotypes (in dhfr, dhps, crt and mdr1) and hrp2 and hrp3 deletions, which have been increasing in recent years. We found no evidence to suggest the emergence of artemisinin (ART) resistance in Peru. These findings indicate a parasite population that is under drug pressure but is susceptible to current antimalarials and demonstrate the added value of a highly multiplexed molecular tool to inform malaria strategies and surveillance systems. IMPORTANCE While the power of next-generation sequencing technologies to inform and guide malaria control programs has become broadly recognized, the integration of genomic data for operational incorporation into malaria surveillance remains a challenge in most countries where malaria is endemic. The main obstacles include limited infrastructure, limited access to high-throughput sequencing facilities, and the need for local capacity to run an in-country analysis of genomes at a large-enough scale to be informative for surveillance. In addition, there is a lack of standardized laboratory protocols and automated analysis pipelines to generate reproducible and timely results useful for relevant stakeholders. With our standardized laboratory and bioinformatic workflow, malaria genetic surveillance data can be readily generated by surveillance researchers and malaria control programs in countries of endemicity, increasing ownership and ensuring timely results for informed decision- and policy-making.

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Statistical modeling of surveillance data to identify correlates of urban malaria risk: A population-based study in the Amazon Basin.

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