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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.

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.

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.

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.

Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them.

The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system.

We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work.