Using Population Mobility Patterns to Adapt COVID-19 Response Strategies in 3 East Africa Countries.

The COVID-19 pandemic spread between neighboring countries through land, water, and air travel. Since May 2020, ministries of health for the Democratic Republic of the Congo, Tanzania, and Uganda have sought to clarify population movement patterns to improve their disease surveillance and pandemic response efforts. Ministry of Health-led teams completed focus group discussions with participatory mapping using country-adapted Population Connectivity Across Borders toolkits. They analyzed the qualitative and spatial data to prioritize locations for enhanced COVID-19 surveillance, community outreach, and cross-border collaboration. Each country employed varying toolkit strategies, but all countries applied the results to adapt their national and binational communicable disease response strategies during the pandemic, although the Democratic Republic of the Congo used only the raw data rather than generating datasets and digitized products. This 3-country comparison highlights how governments create preparedness and response strategies adapted to their unique sociocultural and cross-border dynamics to strengthen global health security.

Planning and implementing a targeted polio vaccination campaign for Somali mobile populations in Northeastern Kenya based on migration and settlement patterns.

Supporting the global eradication of wildpoliovrisu (WPV), this project aimed to provide polio and measles vaccines to a population frequenty missed by immunization services and campaigns, ethnic Somali children living among mobile populations within Kenya's Northeastern Region. Additionally, nutritional support, albendazole (for treatment of intestinal parasites) and vitamin A were provided to improve children's health and in accordance with regional vaccination campaign practices. To better understand movement patterns and healthcare-seeking behaviors within this population, we trained community-based data collectors in qualitative and geospatial data collection methods. Data collectors conducted focus group and participatory mapping discussions with ethnic Somalis living in the region. Qualitative and geospatial data indicated movement patterns that followed partially definable routes and temporary settlement patterns with an influx of ethnic Somali migrants into Kenya at the start of the long rainy season (April-June). Community members also reported concerns about receiving healthcare services in regional health facilities. Using these data, an 8-week vaccination campaign was planned and implemented: 2196 children aged 0-59 months received polio vaccine (9% had not previously received polio vaccine), 2524 children aged 9-59 months received measles vaccine (27% had not previously received measles vaccine), 113 were referred for the treatment of severe acute malnourishment, 150 were referred to a supplementary feeding program due to moderate acute malnourishment, 1636 children aged 12-59 months were provided albendazole and 2008 children aged 6-59 months were provided with vitamin A. This project serves as an example for how community-based data collectors and local knowledge can help adapt public health programming to the local context and could aid disease eradication in at-risk populations.

Farmworker Mobility and COVID-19 Vaccination Strategies: Yuma County, Arizona, 2021.

Farmworkers, a group of essential workers, experience a disproportionately high burden of COVID-19 due to their living and working conditions. This project characterized farmworker mobility in and around Yuma County, Arizona, to identify opportunities to improve farmworker access to COVID-19 vaccination. We collected qualitative and geospatial data through a series of in-person and virtual focus group discussions, key informant interviews, and intercept interviews with participatory mapping. Participants included farmworkers, employers, and representatives of local institutions who serve or interact with farmworkers. We identified participants through purposive and referential sampling and grouped people by sociodemographic characteristics for interviews. We used qualitative and geospatial analyses to identify common themes and mobility patterns. The team interviewed 136 people from February 26 to April 2, 2021. Common themes emerged about how farmworkers have little or no access to COVID-19 vaccination unless offered at their workplaces or at locations where they congregate at convenient times. Further, farmworkers described how their demanding work schedules, long commute times, and caretaker commitments make it challenging to access vaccination services. Geospatial analyses identified three geographic areas in Yuma County where farmworkers reported living and working that did not have a COVID-19 vaccine clinic within walking distance. Coordination between local public health authorities and key partners, including employers and trusted representatives from local community-based organizations or the Mexican consulate, to offer vaccination at worksites or other locations where farmworkers congregate can help improve access to COVID-19 vaccines and booster doses for this population.

Using spatial and population mobility models to inform outbreak response approaches in the Ebola affected area, Democratic Republic of the Congo, 2018-2020.

The Democratic Republic of the Congo's (DRC) 10th known Ebola virus disease (EVD) outbreak occurred between August 1, 2018 and June 25, 2020, and was the largest EVD outbreak in the country's history. During this outbreak, the DRC Ministry of Health initiated traveller health screening at points of control (POC, locations not on the border) and points of entry (POE) to minimize disease translocation via ground and air travel. We sought to develop a model-based approach that could be applied in future outbreaks to inform decisions for optimizing POC and POE placement, and allocation of resources more broadly, to mitigate the risk of disease translocation associated with ground-level population mobility. We applied a parameter-free mobility model, the radiation model, to estimate likelihood of ground travel between selected origin locations (including Beni, DRC) and surrounding population centres, based on population size and drive-time. We then performed a road network route analysis and included estimated population movement results to calculate the proportionate volume of travellers who would move along each road segment; this reflects the proportion of travellers that could be screened at a POC or POE. For Beni, the road segments estimated to have the highest proportion of travellers that could be screened were part of routes into Uganda and Rwanda. Conversely, road segments that were part of routes to other population centres within the DRC were estimated to have relatively lower proportions. We observed a posteriori that, in many instances, our results aligned with locations that were selected for actual POC or POE placement through more time-consuming methods. This study has demonstrated that mobility models and simple spatial techniques can help identify potential locations for health screening at newly placed POC or existing POE during public health emergencies based on expected movement patterns. Importantly, we have provided methods to estimate the proportionate volume of travellers that POC or POE screening measures would assess based on their location. This is critical information in outbreak situations when timely decisions must be made to implement public health interventions that reach the most individuals across a network.

An approach to integrate population mobility patterns and sociocultural factors in communicable disease preparedness and response.

Complex human movement patterns driven by a range of economic, health, social, and environmental factors influence communicable disease spread. Further, cross-border movement impacts disparate public health systems of neighboring countries, making an effective response to disease importation or exportation more challenging. Despite the array of quantitative techniques and social science approaches available to analyze movement patterns, there continues to be a dearth of methods within the applied public health setting to gather and use information about community-level mobility dynamics. Population Connectivity Across Borders (PopCAB) is a rapidly-deployable toolkit to characterize multisectoral movement patterns through community engagement using focus group discussions or key informant interviews, each with participatory mapping, and apply the results to tailor preparedness and response strategies. The Togo and Benin Ministries of Health (MOH), in collaboration with the Abidjan Lagos Corridor Organization and the US Centers for Disease Control and Prevention, adapted and applied PopCAB to inform cross-border preparedness and response strategies for multinational Lassa fever outbreaks. Initially, the team implemented binational, national-level PopCAB activities in March 2017, highlighting details about a circular migration pathway across northern Togo, Benin, and Nigeria. After applying those results to respond to a cross-border Lassa fever outbreak in February 2018, the team designed an expanded PopCAB initiative in April 2018. In eight days, they trained 54 MOH staff who implemented 21 PopCAB focus group discussions in 14 cities with 224 community-level participants representing six stakeholder groups. Using the newly-identified 167 points of interest and 176 routes associated with a circular migration pathway across Togo, Benin, and Nigeria, the Togo and Benin MOH refined their cross-border information sharing and collaboration processes for Lassa fever and other communicable diseases, selected health facilities with increased community connectivity for enhanced training, and identified techniques to better integrate traditional healers in surveillance and community education strategies. They also integrated the final toolkit in national- and district-level public health preparedness plans. Integrating PopCAB in public health practice to better understand and accommodate population movement patterns can help countries mitigate the international spread of disease in support of improved global health security and International Health Regulations requirements.

Preventing the cross-border spread of zoonotic diseases: Multisectoral community engagement to characterize animal mobility-Uganda, 2020.

In Uganda, the borders are highly porous to animal movement, which may contribute to zoonotic disease spread. We piloted an animal adaptation of an existing human-focused toolkit to collect data on animal movement patterns and interactions to inform One Health programs. During January 2020, we conducted focus group discussions and key informant interviews with participatory mapping of 2 national-level One Health stakeholders and 2 local-level abattoir representatives from Kampala. Zoonotic disease hotspots changed in 2020 compared with reports from 2017-2019. In contrast to local-level participants, national-level participants highlighted districts rather than specific locations. Everyone discussed livestock species; only national-level participants mentioned wildlife. Participants described seasonality differently. Stakeholders used the results to identify locations for zoonotic disease interventions and sites for future data collection. This implementation of an animal-adapted population mobility mapping exercise highlights the importance of multisectoral initiatives to promote One Health border health approaches.