Strategies for using antigen rapid diagnostic tests to reduce transmission of SARS-CoV-2 in low- and middle-income countries: a mathematical modelling study applied to Zambia

Background Increasing the availability of antigen rapid diagnostic tests (Ag-RDTs) in low- and middle-income countries (LMICs) is key to alleviating global SARS-CoV-2 testing inequity (median testing rate in December 2021-March 2022 when the Omicron variant was spreading in multiple countries; high-income countries=600 tests/100,000 people/day; LMICs=14 tests/ 100,000 people/day). However, target testing levels and effectiveness of asymptomatic community screening to impact SARS-CoV-2 transmission in LMICs are unclear. Methods We used PATAT, an LMIC-focused agent-based model to simulate COVID-19 epidemics, varying the amount of Ag-RDTs available for symptomatic testing at healthcare facilities and asymptomatic community testing in different social settings. We assumed that testing was a function of access to healthcare facilities and availability of Ag-RDTs. We explicitly modelled symptomatic testing demand from non-SARS-CoV-2 infected individuals and measured impact based on the number of infections averted due to test-and-isolate. Results Testing symptomatic individuals yields greater benefits than any asymptomatic community testing strategy until most symptomatic individuals who sought testing have been tested. Meeting symptomatic testing demand likely requires at least 200-400 tests/100,000 people/day on average as symptomatic testing demand is highly influenced by non-SARS-CoV-2 infected individuals. After symptomatic testing demand is satisfied, excess tests to proactively screen for asymptomatic infections among household members yields the largest additional infections averted. Conclusions Testing strategies aimed at reducing transmission should prioritize symptomatic testing and incentivizing test-positive individuals to adhere to isolation to maximize effectiveness. ### Competing Interest Statement J.A.S., A.T., N.H., E.H. and B.E.N. were employed by FIND, the global alliance for diagnostics. ### Funding Statement A.X.H. and C.A.R. were supported by ERC NaviFlu (No. 818353). C.A.R. was also supported by NIH R01 (5R01AI132362-04) and an NWO Vici Award (09150182010027). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes All data relevant to the study are included in the Article, the Supplementary Appendix and the GitHub repository (). The PATAT model source code can also be found in the GitHub repository ().