Multiple Anopheles species complicate downstream analysis and decision-making in a malaria pre-elimination area in southern Mozambique.

BACKGROUND: Different anopheline species (even within a species group/complex) can differ in their feeding and resting behaviours, which impact both malaria transmission patterns as well as the efficacy of vector control interventions. While morphological identification of sampled specimens is an important first step towards understanding species diversity and abundance, misidentification can result in the implementation of less effective vector control measures, and consequently smaller reductions in the number of local malaria cases. Focusing on southern Mozambique, a malaria pre-elimination area where malaria remains persistent, the aims of this preliminary study were to use molecular identification (CO1 and ITS2 barcoding) to (1) validate the results from the morphological identification (with a particular focus on Anopheles pharoensis and Anopheles squamosus), and (2) have a closer look at the Anopheles coustani group (which includes Anopheles tenebrosus and Anopheles ziemanni). METHODS: Female anopheline mosquitoes (n = 81) were identified morphologically and subsequently sequenced at the ribosomal DNA internal transcribed spacer region 2 (ITS2) and/or cytochrome oxidase subunit 1 (CO1) loci towards species determination. RESULTS: Out of the 62 specimens that were identified morphologically to species, 4 (6.5%) were misidentified. Regarding the An. coustani group, morphological identification showed that several members are present in southern Mozambique, including An. coustani sensu lato (s.l.), An. ziemanni and An. tenebrosus. However, based on both ITS2 and CO1 sequences, the exact species remains unknown for the latter two members until voucher sequences are available for comparison. CONCLUSION: The reason(s) for morphological misidentification of anopheline mosquitoes need to be mitigated. This is usually related to both the capacity (i.e. training) of the microscopist to identify anopheline species, and the information provided in the dichotomous identification key. As the An. coustani complex contributes to (residual) malaria transmission in sub-Saharan Africa, it may play a role in the observed persistent malaria in southern Mozambique. A better baseline characterizing of the local anophelines species diversity and behaviours will allow us to improve entomological surveillance strategies, better understand the impact of vector control on each local vector species, and identify new approaches to target those vector species.

Improving the Quality and Use of Malaria Surveillance Data: Results from Evaluating an Integrated Malaria Information Storage System at the Health Facility Level in Selected Districts in Mozambique.

Mozambique addressed critical malaria surveillance system challenges by rolling out an integrated malaria information storage system (iMISS) at the district level in February 2021. The iMISS integrates malaria data from existing systems across thematic program areas to improve data availability and use. In seven districts, the platform was extended to health facilities (HFs), allowing HFs to access iMISS and use tablets to submit monthly malaria reports to a central database, eliminating the need for paper-based reporting to districts. A structured evaluation of the iMISS rollout to HFs was carried out in February-July 2021. The four evaluation areas were data quality (reporting rate, timeliness, and fidelity) of monthly malaria reports electronically submitted to the iMISS, adoption of the iMISS for data-informed decision-making, system maintenance, and acceptability of the iMISS among target users. All 94 HFs in the seven targeted districts were assessed. Over the 6-month period, 86.1% of reported cases on the iMISS were consistent with cases recorded in paper-based reports, allowing for up to 10% discrepancy. In addition, 69.0% of expected monthly district meetings were held, and information from iMISS was discussed during 58.6% of these meetings. Maintenance issues, mostly related to tablet access and internet connectivity, were experienced by 74.5% of HFs; 33.7% of issues were resolved within 1 month. The iMISS and electronic submission of malaria reports were well accepted by HF- and district-level users. Continued political commitment and timely execution of issue management workflows are crucial to ensure trust in the new platform and facilitate higher levels of data use.

Improving the Quality and Use of Malaria Surveillance Data: Results from Evaluating an Integrated Malaria Information Storage System at the Health Facility Level in Selected Districts in Mozambique

Mozambique addressed critical malaria surveillance system challenges by rolling out an integrated malaria information storage system (iMISS) at the district level in February 2021. The iMISS integrates malaria data from existing systems across thematic program areas to improve data availability and use. In seven districts, the platform was extended to health facilities (HFs), allowing HFs to access iMISS and use tablets to submit monthly malaria reports to a central database, eliminating the need for paper-based reporting to districts. A structured evaluation of the iMISS rollout to HFs was carried out in February-July 2021. The four evaluation areas were data quality (reporting rate, timeliness, and fidelity) of monthly malaria reports electronically submitted to the iMISS, adoption of the iMISS for data-informed decision-making, system maintenance, and acceptability of the iMISS among target users. All 94 HFs in the seven targeted districts were assessed. Over the 6-month period, 86.1% of reported cases on the iMISS were consistent with cases recorded in paper-based reports, allowing for up to 10% discrepancy. In addition, 69.0% of expected monthly district meetings were held, and information from iMISS was discussed during 58.6% of these meetings. Maintenance issues, mostly related to tablet access and internet connectivity, were experienced by 74.5% of HFs; 33.7% of issues were resolved within 1 month. The iMISS and electronic submission of malaria reports were well accepted by HF- and district-level users. Continued political commitment and timely execution of issue management workflows are crucial to ensure trust in the new platform and facilitate higher levels of data use.

Optimizing Routine Malaria Surveillance Data in Urban Environments: A Case Study in Maputo City, Mozambique.

In urban settings in malaria-endemic countries, malaria incidence is not well characterized and assumed to be typically very low and consisting largely of imported infections. In such contexts, surveillance systems should adapt to ensure that data are of sufficient spatial and temporal resolution to inform appropriate programmatic interventions. The aim of this research was to 1) assess spatial and temporal trends in reported malaria cases in Maputo City, Mozambique, using an expanded case notification form and 2) to determine how malaria surveillance can be optimized to characterize the local epidemiological context, which can then be used to inform targeted entomological investigations and guide implementation of localized malaria responses. This study took place in all six health facilities of KaMavota District in Maputo City, Mozambique. A questionnaire was administered to all confirmed cases from November 2019 to August 2021. Households of cases were retrospectively geolocated using local landmarks as reference. Overall, 2,380 malaria cases were reported, with the majority being uncomplicated (97.7%) and a median age of 21 years; 70.8% of cases had reported traveling outside the city in the past month with nine reporting traveling internationally. Maps of the 1,314 malaria cases that were geolocated showed distinct spatial patterns. The expanded case notification form enables a more granular overview of the malaria epidemiology in Maputo City; the geolocation data clearly show the areas where endemic transmission is likely, thus informing where resources should be prioritized. As urbanization is rapidly increasing in malaria endemic areas, identifying systems and key variables to collect ensures an operational way to characterize urban malaria through optimization of routine data to inform decision-making.