tetano
Editor, Senior Moderator
Emerg Infect Dis
. 2022;28(13):105-113.
doi: 10.3201/eid2813.220848.
Using Population Mobility Patterns to Adapt COVID-19 Response Strategies in 3 East Africa Countries
Rebecca D Merrill, Fadhili Kilamile, Mwabi White, Daniel Eurien, Kanan Mehta, Joseph Ojwang, Marianne Laurent-Comlan, Peter Ahabwe Babigumira, Lydia Nakiire, Alexandra Boos, Wangeci Gatei, Julie R Harris, Alain Magazani, Felix Ocom, Robert Ssekubugu, Godfrey Kigozi, Florent Senyana, Francis B Iyese, Peter James Elyanu, Sarah Ward, Issa Makumbi, Allan Muruta, Elvira McIntyre, Khalid Massa, Alex R Ario, Harriet Mayinja, Kakulu Remidius, Dede N Ndungi
Abstract
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.
Keywords: COVID-19; DRC; Democratic Republic of the Congo; PopCAB; SARS-CoV-2; Tanzania; Uganda; border crossing; community networks; coronavirus disease; international health; population dynamics; respiratory infections; severe acute respiratory syndrome coronavirus 2; viruses; zoonoses.
. 2022;28(13):105-113.
doi: 10.3201/eid2813.220848.
Using Population Mobility Patterns to Adapt COVID-19 Response Strategies in 3 East Africa Countries
Rebecca D Merrill, Fadhili Kilamile, Mwabi White, Daniel Eurien, Kanan Mehta, Joseph Ojwang, Marianne Laurent-Comlan, Peter Ahabwe Babigumira, Lydia Nakiire, Alexandra Boos, Wangeci Gatei, Julie R Harris, Alain Magazani, Felix Ocom, Robert Ssekubugu, Godfrey Kigozi, Florent Senyana, Francis B Iyese, Peter James Elyanu, Sarah Ward, Issa Makumbi, Allan Muruta, Elvira McIntyre, Khalid Massa, Alex R Ario, Harriet Mayinja, Kakulu Remidius, Dede N Ndungi
- PMID: 36502402
- DOI: 10.3201/eid2813.220848
Abstract
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.
Keywords: COVID-19; DRC; Democratic Republic of the Congo; PopCAB; SARS-CoV-2; Tanzania; Uganda; border crossing; community networks; coronavirus disease; international health; population dynamics; respiratory infections; severe acute respiratory syndrome coronavirus 2; viruses; zoonoses.