Prioritizing COVID-19 tests based on participatory surveillance and spatial scanning.

OBJECTIVES: This study aimed to identify, describe and analyze priority areas for COVID-19 testing combining participatory surveillance and traditional surveillance. DESIGN: It was carried out a descriptive transversal study in the city of Caruaru, Pernambuco state, Brazil, within the period of 20/02/2020 to 05/05/2020. Data included all official reports for influenza-like illness notified by the municipality health department and the self-reports collected through the participatory surveillance platform Brasil Sem Corona. METHODS: We used linear regression and loess regression to verify a correlation between Participatory Surveillance (PS) and Traditional Surveillance (TS). Also a spatial scanning approach was deployed in order to identify risk clusters for COVID-19. RESULTS: In Caruaru, the PS had 861 active users, presenting an average of 1.2 reports per user per week. The platform Brasil Sem Corona started on March 20th and since then, has been officially used by the Caruaru health authority to improve the quality of information from the traditional surveillance system. Regarding the respiratory syndrome cases from TS, 1588 individuals were positive for this clinical outcome. The spatial scanning analysis detected 18 clusters and 6 of them presented statistical significance (p-value < 0.1). Clusters 3 and 4 presented an overlapping area that was chosen by the local authority to deploy the COVID-19 serology, where 50 individuals were tested. From there, 32 % (n = 16) presented reagent results for antibodies related to COVID-19. CONCLUSION: Participatory surveillance is an effective epidemiological method to complement the traditional surveillance system in response to the COVID-19 pandemic by adding real-time spatial data to detect priority areas for COVID-19 testing.

A correct formulation for a spatially implicit predator-prey metacommunity model.

In order to mitigate the problem of increasing model complexity with increasing number of occupation states in spatially implicit metacommunity models, the assumption of independency among species distributions is often required. In the present paper, we show that this approach only works correctly if set relations among patch occupancy states are considered adequately. This is illustrated by means of a well-known, although incorrectly formulated, predator-prey metacommunity model devised by Bascompte and Solé[1]. We demonstrate that this model shows anomalous dynamical behavior caused by inconsistence between the model formulation and its assumptions. In order to formalize our finding we develop a corrected model formulation that accounts for the principles of set theory so that the sum of the system compartments change rate is nulled. Applying this method successfully rules out the occurrence of anomalous dynamical behavior found in the original model. Finally we discuss the implications of our findings for the accuracy of model predictions.