TY - JOUR
T1 - Combining rapid antigen testing and syndromic surveillance improves community-based COVID-19 detection in a low-income country
AU - Chadwick, Fergus J.
AU - Clark, Jessica
AU - Chowdhury, Shayan
AU - Chowdhury, Tasnuva
AU - Pascall, David J.
AU - Haddou, Yacob
AU - Andrecka, Joanna
AU - Kundegorski, Mikolaj
AU - Wilkie, Craig
AU - Brum, Eric
AU - Shirin, Tahmina
AU - Alamgir, A. S. M.
AU - Rahman, Mahbubur
AU - Alam, Ahmed Nawsher
AU - Khan, Farzana
AU - Swallow, Ben
AU - Mair, Frances S.
AU - Illian, Janine
AU - Trotter, Caroline L.
AU - Hill, Davina L.
AU - Husmeier, Dirk
AU - Matthiopoulos, Jason
AU - Hampson, Katie
AU - Sania, Ayesha
N1 - This work is supported by a grant from the Bill and Melinda Gates Foundation to FAO (INV-022851). F.J.C. is funded by EPSRC (EP/R513222/1), D.J.P. by the JUNIPER consortium (MR/V038613/1) and K.H. by Wellcome (207569/Z/17/Z).
PY - 2022/5/26
Y1 - 2022/5/26
N2 - Diagnostics for COVID-19 detection are limited in many settings. Syndromic surveillance is often the only means to identify cases but lacks specificity. Rapid antigen testing is inexpensive and easy-to-deploy but can lack sensitivity. We examine how combining these approaches can improve surveillance for guiding interventions in low-income communities in Dhaka, Bangladesh. Rapid-antigen-testing with PCR validation was performed on 1172 symptomatically-identified individuals in their homes. Statistical models were fitted to predict PCR-status using rapid-antigen-test results, syndromic data, and their combination. Under contrasting epidemiological scenarios, the models’ predictive and classification performance was evaluated. Models combining rapid-antigen-testing and syndromic data yielded equal-to-better performance to rapid-antigen-test-only models across all scenarios with their best performance in the epidemic growth scenario. These results show that drawing on complementary strengths across rapid diagnostics, improves COVID-19 detection, and reduces false-positive and -negative diagnoses to match local requirements; improvements achievable without additional expense, or changes for patients or practitioners.
AB - Diagnostics for COVID-19 detection are limited in many settings. Syndromic surveillance is often the only means to identify cases but lacks specificity. Rapid antigen testing is inexpensive and easy-to-deploy but can lack sensitivity. We examine how combining these approaches can improve surveillance for guiding interventions in low-income communities in Dhaka, Bangladesh. Rapid-antigen-testing with PCR validation was performed on 1172 symptomatically-identified individuals in their homes. Statistical models were fitted to predict PCR-status using rapid-antigen-test results, syndromic data, and their combination. Under contrasting epidemiological scenarios, the models’ predictive and classification performance was evaluated. Models combining rapid-antigen-testing and syndromic data yielded equal-to-better performance to rapid-antigen-test-only models across all scenarios with their best performance in the epidemic growth scenario. These results show that drawing on complementary strengths across rapid diagnostics, improves COVID-19 detection, and reduces false-positive and -negative diagnoses to match local requirements; improvements achievable without additional expense, or changes for patients or practitioners.
U2 - 10.1038/s41467-022-30640-w
DO - 10.1038/s41467-022-30640-w
M3 - Article
SN - 2041-1723
VL - 13
JO - Nature Communications
JF - Nature Communications
M1 - 2877
ER -
