Using antenatal care as a platform for malaria surveillance data collection: study protocol

BACKGROUND: While many malaria-endemic countries have health management information systems that can measure and report malaria trends in a timely manner, these routine systems have limitations. Periodic community cross-sectional household surveys are used to estimate malaria prevalence and intervention coverage but lack geographic granularity and are resource intensive. Incorporating malaria testing for all women at their first antenatal care (ANC) visit (i.e., ANC1) could provide a more timely and granular source of data for monitoring trends in malaria burden and intervention coverage. This article describes a protocol designed to assess if ANC-based surveillance could be a pragmatic tool to monitor malaria. METHODS: This is an observational, cross-sectional study conducted in Benin, Burkina Faso, Mozambique, Nigeria, Tanzania, and Zambia. Pregnant women attending ANC1 in selected health facilities will be tested for malaria infection by rapid diagnostic test and administered a brief questionnaire to capture key indicators of malaria control intervention coverage and care-seeking behaviour. In each location, contemporaneous cross-sectional household surveys will be leveraged to assess correlations between estimates obtained using each method, and the use of ANC data as a tool to track trends in malaria burden and intervention coverage will be validated. RESULTS: This study will assess malaria prevalence at ANC1 aggregated at health facility and district levels, and by gravidity relative to current pregnancy (i.e., gravida 1, gravida 2, and gravida 3 +). ANC1 malaria prevalence will be presented as monthly trends. Additionally, correlation between ANC1 and household survey-derived estimates of malaria prevalence, bed net ownership and use, and care-seeking will be assessed. CONCLUSION: ANC1-based surveillance has the potential to provide a cost-effective, localized measure of malaria prevalence that is representative of the general population and useful for tracking monthly changes in parasite prevalence, as well as providing population-representative estimates of intervention coverage and care-seeking behavior. This study will evaluate the representativeness of these measures and collect information on operational feasibility, usefulness for programmatic decision-making, and potential for scale-up of malaria ANC1 surveillance

Design and methods for a quasi-experimental pilot study to evaluate the impact of dual active ingredient insecticide-treated nets on malaria burden in five regions in sub-Saharan Africa

Background Vector control tools have contributed significantly to a reduction in malaria burden since 2000, primarily through insecticidal-treated bed nets (ITNs) and indoor residual spraying. In the face of increasing insecticide resistance in key malaria vector species, global progress in malaria control has stalled. Innovative tools, such as dual active ingredient (dual-AI) ITNs that are effective at killing insecticide-resistant mosquitoes have recently been introduced. However, large-scale uptake has been slow for several reasons, including higher costs and limited evidence on their incremental effectiveness and cost-effectiveness. The present report describes the design of several observational studies aimed to determine the effectiveness and cost-effectiveness of dual-AI ITNs, compared to standard pyrethroid-only ITNs, at reducing malaria transmission across a variety of transmission settings. Methods Observational pilot studies are ongoing in Burkina Faso, Mozambique, Nigeria, and Rwanda, leveraging dual-AI ITN rollouts nested within the 2019 and 2020 mass distribution campaigns in each country. Enhanced surveillance occurring in select study districts include annual cross-sectional surveys during peak transmission seasons, monthly entomological surveillance, passive case detection using routine health facility surveillance systems, and studies on human behaviour and ITN use patterns. Data will compare changes in malaria transmission and disease burden in districts receiving dual-AI ITNs to similar districts receiving standard pyrethroid-only ITNs over three years. The costs of net distribution will be calculated using the provider perspective including financial and economic costs, and a cost-effectiveness analysis will assess incremental cost-effectiveness ratios for Interceptor® G2, Royal Guard®, and piperonyl butoxide ITNs in comparison to standard pyrethroid-only ITNs, based on incidence rate ratios calculated from routine data. Conclusions Evidence of the effectiveness and cost-effectiveness of the dual-AI ITNs from these pilot studies will complement evidence from two contemporary cluster randomized control trials, one in Benin and one in Tanzania, to provide key information to malaria control programmes, policymakers, and donors to help guide decision-making and planning for local malaria control and elimination strategies. Understanding the breadth of contexts where these dual-AI ITNs are most effective and collecting robust information on factors influencing comparative effectiveness could improve uptake and availability and help maximize their impact

An open-source python library for detection of known and novel Kell, Duffy and Kidd variants from exome sequencing

Background and objectives: Next generation sequencing (NGS) has promising applications in transfusion medicine. Exome sequencing (ES) is increasingly used in the clinical setting, and blood group interpretation is an additional value that could be extracted from existing data sets. We provide the first release of an open-source software tailored for this purpose and describe its validation with three blood group systems. Materials and methods: The DTM-Tools algorithm was designed and used to analyse 1018 ES NGS files from the ClinSeq® cohort. Predictions were correlated with serology for 5 antigens in a subset of 108 blood samples. Discrepancies were investigated with alternative phenotyping and genotyping methods, including a long-read NGS platform. Results: Of 116 genomic variants queried, those corresponding to 18 known KEL, FY and JK alleles were identified in this cohort. 596 additional exonic variants were identified KEL, ACKR1 and SLC14A1, including 58 predicted frameshifts. Software predictions were validated by serology in 108 participants; one case in the FY blood group and three cases in the JK blood group were discrepant. Investigation revealed that these discrepancies resulted from (1) clerical error, (2) serologic failure to detect weak antigenic expression and (3) a frameshift variant absent in blood group databases. Conclusion: DTM-Tools can be employed for rapid Kell, Duffy and Kidd blood group antigen prediction from existing ES data sets; for discrepancies detected in the validation data set, software predictions proved accurate. DTM-Tools is open-source and in continuous development. © 2020 International Society of Blood Transfusio