Application of the ARIMA Model to Predict Under-Reporting of New Cases of Hansen's Disease during the COVID-19 Pandemic in a Municipality of the Amazon Region.

This work aimed to apply the ARIMA model to predict the under-reporting of new Hansen's disease cases during the COVID-19 pandemic in Palmas, Tocantins, Brazil. This is an ecological time series study of Hansen's disease indicators in the city of Palmas between 2001 and 2020 using the autoregressive integrated moving averages method. Data from the Notifiable Injuries Information System and population estimates from the Brazilian Institute of Geography and Statistics were collected. A total of 7035 new reported cases of Hansen's disease were analyzed. The ARIMA model (4,0,3) presented the lowest values for the two tested information criteria and was the one that best fit the data, as AIC = 431.30 and BIC = 462.28, using a statistical significance level of 0.05 and showing the differences between the predicted values and those recorded in the notifications, indicating a large number of under-reporting of Hansen's disease new cases during the period from April to December 2020. The ARIMA model reported that 177% of new cases of Hansen's disease were not reported in Palmas during the period of the COVID-19 pandemic in 2020. This study shows the need for the municipal control program to undertake immediate actions in terms of actively searching for cases and reducing their hidden prevalence.

Computing and Oral Health: Mobile Solution for Collecting, Data Analysis, Managing and Reproducing Epidemiological Research in Population Groups.

Epidemiological inquiries study and evaluate the health status of the population. For dental caries, the World Health Organization (WHO) recommends the DMFT and DMFS indexes, which represent the sum of the decayed, missing and filled teeth, divided by the population studied. Traditionally these surveys are conducted using cellulose paper sheet. This study describes the development and presents the field performance of NutriOdonto, a software created for an Oral Health Survey carried out in 2018 and 2019 involving 2578 students from the municipal schools of Palmas/TO, located in the Brazilian Amazon region. This is a descriptive, applied research on the development of a software for the collecting, analysis, management and reproducibility of oral health epidemiological research. A software applied to the collecting, analysis and formation of the database was developed through the information obtained from the questionnaires applied to the participants of the study and the completion of the electronic oral examination form. Recent Information and Communication Technologies (ICT) are intelligently configured to create models and mobile applications (Apps) that can be useful to manage health issues, thus broadening the perspective of service provision in this sector. Some of these mobile devices, tablets and smartphones are being developed to generate information, for collection, recording, storage and analysis of oral health epidemiological research data. NutriOdonto contributed to the rapid collection, recording and storage of information, in the construction of the database and its analysis. Replacing paper forms with electronic forms minimized possible typos, reduced the use of cellulose paper and the financial costs, among other things. This software can contribute to decision making by managers and professionals and to improving the planning and implementation of actions in health promotion and oral disease prevention.