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Background: Human mobility is a driver for the reemergence or resurgence of malaria and has been identified as a source of cross-border transmission. However, movement patterns are difficult to measure in rural areas where malaria risk is high. In countries with malaria elimination goals, it is essential to determine the role of mobility on malaria transmission to implement appropriate interventions. Methods: A study was conducted in Mutasa District, Zimbabwe, to investigate human movement patterns in an area of persistent transmission along the Mozambique border. Over 1 year, a convenience sample of 20 participants/month was recruited from active malaria surveillance cohorts to carry an IgotU® GT-600 global positioning system (GPS) data logger during all daily activities. Consenting participants were tested for malaria at data logger distribution using rapid antigen diagnostic tests and completed a survey questionnaire. GPS data were analyzed using a trajectory analysis tool, and participant movement patterns were characterized throughout the study area and across the border into Mozambique using movement intensity maps, activity space plots, and statistical analyses. Results: From June 2016–May 2017, 184 participants provided movement tracks encompassing > 350,000 data points and nearly 8000 person-days. Malaria prevalence at logger distribution was 3.7%. Participants traveled a median of 2.8 km/day and spent a median of 4.6 h/day away from home. Movement was widespread within and outside the study area, with participants traveling up to 500 km from their homes. Indices of mobility were higher in the dry season than the rainy season (median km traveled/day = 3.5 vs. 2.2, P = 0.03), among male compared to female participants (median km traveled/day = 3.8 vs. 2.0, P = 0.0008), and among adults compared to adolescents (median total km traveled = 104.6 vs. 59.5, P = 0.05). Half of participants traveled outside the study area, and 30% traveled into Mozambique, including 15 who stayed in Mozambique overnight. Conclusions: Study participants in Mutasa District, Zimbabwe, were highly mobile throughout the year. Many participants traveled long distances from home, including overnight trips into Mozambique, with clear implications for malaria control. Interventions targeted at mobile populations and cross-border transmission may be effective in preventing malaria introductions in this region. [ABSTRACT FROM AUTHOR]

Cross-border human population movement contributes to malaria transmission in border regions, impeding national elimination. However, its impact in low-to-moderate transmission settings is not well characterized. This community-based study in Mutasa District, Zimbabwe, estimated the association of parasite prevalence with self-reported overnight travel to Mozambique and household distance to the border from 2012-2020. A fully adjusted Poisson regression model with robust variance estimation was fit using active surveillance data. The population attributable fraction of parasite prevalence from overnight travel was also estimated. The relative risk of testing positive for malaria by rapid diagnostic test declined 14% (prevalence ratio [PR] = 0.86, 95% CI = 0.81-0.92) per kilometer from the border up to 12 km away. Travel to Mozambique was associated with a 157% increased risk (PR = 2.57, 95% CI = 1.38-4.78), although only 5.8% of cases were attributable to overnight travel (95% CI = -1.1% to 12.7%), reflecting infrequent overnight trips (1.3% of visits). This study suggests that transmission in eastern Zimbabwe is driven by increasingly conducive social or environmental conditions approaching the border and low levels of importation from overnight travel. Although day trips to Mozambique during peak biting hours were not assessed, the contribution of such trips to ongoing transmission may be significant. Future malaria control efforts should prioritize high coverage of existing interventions and continued support for community health workers and health facilities at the border, which provide free case management.

Background: In 2019, South Africa, Nigeria, Tanzania, Democratic Republic of Congo, Uganda, Mozambique, Zambia, Angola, Cameroon, Zimbabwe, Ghana, Ethiopia, Malawi, Kenya, South Sudan and Côte d'Ivoire accounted for 80% of children living with HIV (CLHIV) not receiving HIV treatment. This manuscript describes pediatric HIV testing to inform case-finding strategies., Methods: We analyzed US President's Emergency Plan for AIDS Relief monitoring, evaluation, and reporting data (October 1, 2018 to September 30, 2019) for these 16 countries. Number of HIV tests and positive results were reported by age band, country, treatment coverage and testing modality. The number needed to test (NNT) to identify 1 new CLHIV 1-14 years was measured by testing modality and country. The pediatric testing gap was estimated by multiplying the estimated number of CLHIV unaware of their status by NNT per country., Results: Among children, 6,961,225 HIV tests were conducted, and 101,762 CLHIV were identified (NNT 68), meeting 17.6% of the pediatric testing need. Index testing accounted for 13.0% of HIV tests (29.7% of positive results, NNT 30), provider-initiated testing and counseling 65.9% of tests (43.6% of positives, NNT 103), and universal testing at sick entry points 5.3% of tests (6.5% of positives, NNT 58)., Conclusions: As countries near HIV epidemic control for adults, the need to increase pediatric testing continues. Each testing modality - PITC, universal testing at sick entry points, and index testing - offers unique benefits. These results illustrate the comparative advantages of including a strategic mix of testing modalities in national programs to increase pediatric HIV case finding., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)