Introduction:

During the occurrence of ongoing emerging infectious diseases such as COVID-19, spatiotemporal surveillance is crucial to identify priority areas for specific interventions, differentiate diagnostic intensity and assign resources.

Objective:

To model the evolution of the relative risk of presentation of COVID-19 cases and to identify clusters in municipalities where the disease remains at the stage following the descent of the epidemic curve in Cuba.

Methods:

The period mentioned was from 26/05/2020 to 4/09/2020. Cyclic runs of Poisson's prospective spatiotemporal model were performed, with progressive 14-day increases, using the software SaTScan™ 9.6.

Results:

A total 15 significant clusters were identified (p ≤ 0.0001) extending over one to thirteen municipalities and distributed in six provinces (Pinar del Río, Artemisa, Havana, Mayabeque, Matanzas, Villa Clara and Ciego de Ávila). In the clusters, all municipalities showed a high relative risk among them, La Palma in Pinar del Rio province and Ciego de Avila in the province of the same name, with the highest values, 119.95 and 121.04, respectively.

Conclusion:

The model was able to identify territories with a significant likelihood of COVID-19 occurrence, as well as periods in the evolution of relative risk. It also showed that surveillance and early warning strategies may facilitate prioritization of health control and containment interventions aimed at preventing the reemergence of the disease with greater spatial coverage.

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