Evans M. V. auteur aut IRD Ramiadantsoa Tanjona auteur aut IRD Kauffman K. auteur aut IRD Moody J. auteur aut IRD Nunn C. L. auteur aut IRD Rabezara J. Y. auteur aut IRD Raharimalala P. auteur aut IRD Randriamoria T. M. auteur aut IRD Soarimalala V. auteur aut IRD Titcomb G. auteur aut IRD Garchitorena Andres auteur aut IRD Roche Benjamin auteur aut IRD text journalArticle eng text/pdf born digital access In empirical social networks from rural Madagascar, epidemic simulations show that targeted testing guided by sociodemographic characteristics controls epidemics as effectively as targeted testing guided by known social network characteristics. Background Targeted surveillance allows public health authorities to implement testing and isolation strategies when diagnostic resources are limited, and can be implemented via the consideration of social network topologies. However, it remains unclear how to implement such surveillance and control when network data are unavailable. Methods We evaluated the ability of sociodemographic proxies of degree centrality to guide prioritized testing of infected individuals compared to known degree centrality. Proxies were estimated via readily available sociodemographic variables (age, gender, marital status, educational attainment, household size). We simulated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemics via a susceptible-exposed-infected-recovered individual-based model on 2 contact networks from rural Madagascar to test applicability of these findings to low-resource contexts. Results Targeted testing using sociodemographic proxies performed similarly to targeted testing using known degree centralities. At low testing capacity, using proxies reduced infection burden by 22%-33% while using 20% fewer tests, compared to random testing. By comparison, using known degree centrality reduced the infection burden by 31%-44% while using 26%-29% fewer tests. Conclusions We demonstrate that incorporating social network information into epidemic control strategies is an effective countermeasure to low testing capacity and can be implemented via sociodemographic proxies when social network data are unavailable. specialized COVID-19 Madagascar epidemic control social network MADAGASCAR 050 020 052 [Early access] [9 p.] 2023 0022-1899 https://www.documentation.ird.fr/hor/fdi:010087646 10.1093/infdis/jiad076 0022-1899 [F B010087646] https://www.documentation.ird.fr/hor/fdi:010087646 https://www.documentation.ird.fr/intranet/publi/2023-06/010087646.pdf Accès réservé (Intranet de l'IRD) IRD - Base Horizon / Pleins textes 2023-06-30 2023-06-30 fdi:010087646 fre