Table 11.

Future work key points.

An adequate response to the COVID-19 pandemic demands a fine-grained understanding of the population under study, since interventions have disparate effects on target populations, depending on multiple factors [28]. Since variation in the outcomes of pandemic interventions involves allocating extremely limited resources to different population sectors elicit different outcomes, the CDS platform may be used as a valuable tool to optimize resource allocation.

Having a limited supply of COVID-19 tests is not a constraint unique to San Luis Potosí. Whatever few tests available used to diagnose those already with symptoms is not as informative when 40%–45% of those infected with SARS-CoV-2 will remain asymptomatic and the potential of the virus to spread silently may be significant [29]. Whereas extensive contact tracing via testing has been successful in South Korea and other countries, such a scale of testing is infeasible in Mexico. One possible solution involves using heterogeneous population factors to decide how to allocate tests differentially [30]. This approach may profit from using a tool as CDS to quantify risk and different citizen profiles in diverse geographies.

Information on the spatial distribution of cases during the spread of transmissible diseases is crucial to design and execute effective interventions. The CDS platform allows documentation and exploration of COVID-19 risk self-assessment data to enable epidemiological intelligence tasks, and may be extended to address epidemiological events concurrent with COVID-19, such as the next expected influenza A and B outbreaks. Survey data could also provide useful information to allocate vaccination campaigns across the state of San Luis Potosí and elsewhere.