Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/37012
Title: The secondary transmission pattern of COVID-19 based on contact tracing in Rwanda
Authors: SEMAKULA, Muhammed 
Niragire, FranCois
Umutoni, Angela
Nsanzimana, Sabin
Ndahindwa, Vedaste
Rwagasore, Edison
Nyatanyi, Thierry
Remera, Eric
FAES, Christel 
Issue Date: 2021
Publisher: BMJ PUBLISHING GROUP
Source: BMJ Global Health, 6 (6) (Art N° e004885)
Abstract: Introduction COVID-19 has shown an exceptionally high spread rate across and within countries worldwide. Understanding the dynamics of such an infectious disease transmission is critical for devising strategies to control its spread. In particular, Rwanda was one of the African countries that started COVID-19 preparedness early in January 2020, and a total lockdown was imposed when the country had only 18 COVID-19 confirmed cases known. Using intensive contact tracing, several infections were identified, with the majority of them being returning travellers and their close contacts. We used the contact tracing data in Rwanda for understanding the geographic patterns of COVID-19 to inform targeted interventions. Methods We estimated the attack rates and identified risk factors associated to COVID-19 spread. We used Bayesian disease mapping models to assess the spatial pattern of COVID-19 and to identify areas characterised by unusually high or low relative risk. In addition, we used multiple variable conditional logistic regression to assess the impact of the risk factors. Results The results showed that COVID-19 cases in Rwanda are localised mainly in the central regions and in the southwest of Rwanda and that some clusters occurred in the northeast of Rwanda. Relationship to the index case, being male and coworkers are the important risk factors for COVID-19 transmission in Rwanda. Conclusion The analysis of contact tracing data using spatial modelling allowed us to identify high-risk areas at subnational level in Rwanda. Estimating risk factors for infection with SARS-CoV-2 is vital in identifying the clusters in low spread of SARS-CoV-2 subnational level. It is imperative to understand the interactions between the index case and contacts to identify superspreaders, risk factors and high-risk places. The findings recommend that self-isolation at home in Rwanda should be reviewed to limit secondary cases from the same households and spatiotemporal analysis should be introduced in routine monitoring of COVID-19 in Rwanda for policy making decision on real time.
Notes: Semakula, M (corresponding author), Univ Rwanda, Ctr Excellence Data Sci, Kigali Campus, Kigali, Rwanda.; Semakula, M (corresponding author), Hasselt Biostat & Stat Bioinformat Ctr, Ctr Stat, Diepenbeek, Limburg, Belgium.
semakulam@gmail.com
Keywords: COVID-19;epidemiology
Document URI: http://hdl.handle.net/1942/37012
ISSN: 2059-7908
e-ISSN: 2059-7908
DOI: 10.1136/bmjgh-2020-004885
ISI #: WOS:000764170600005
Rights: Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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