RESUMO
During crises such as the present coronavirus disease-19 (COVID-19) pandemic, nonprofits play a key role in ensuring support to improve the most vulnerable individuals' health, social, and economic conditions. One year into the COVID-19 pandemic, an extensive automated literature analysis was conducted of 154 academic articles on nonprofit management during the pandemic-all of which were published in 2020. This study sought to identify and systematize academics' contributions to knowledge about the crisis's impact on the nonprofit sector and to ascertain the most urgent directions for future research. The results provide policymakers, nonprofit practitioners, and scholars an overview of the themes addressed and highlight the important assistance academic researchers provide to nonprofits dealing with the COVID-19 pandemic. Supplementary Information: The online version contains supplementary material available at 10.1007/s11266-021-00432-9.
RESUMO
The success of screening programs depends to a large extent on the adherence of the target population, so it is therefore of fundamental importance to develop computer simulation models that make it possible to understand the factors that correlate with this adherence, as well as to identify population groups with low adherence to define public health strategies that promote behavioral change. Our aim is to demonstrate that it is possible to simulate screening adherence behavior using computer simulations. Three versions of an agent-based model are presented using different methods to determine the agent's individual decision to adhere to screening: (a) logistic regression; (b) fuzzy logic components and (c) a combination of the previous. All versions were based on real data from 271,867 calls for diabetic retinopathy screening. The results obtained are statistically very close to the real ones, which allows us to conclude that despite having a high degree of abstraction from the real data, the simulations are very valid and useful as a tool to support decisions in health planning, while evaluating multiple scenarios and accounting for emergent behavior.