Distribuição geoespacial dos casos de covid-19 em Mato Grosso, perfil epidemiológico e clínico de indivíduos recuperados da infecção no Vale do São Lourenço

Abstract

The COVID-19 pandemic has impacted public health systems worldwide, affecting the quality of life of several population groups. This research used spatiotemporal analyses to examine COVID-19 cases and deaths distribution in Mato Grosso State between 2020 and 2023 using secondary data from IndicaSUS. During this period, a total of 879,706 cases were recorded, with notable regional disparities. Women had a slightly higher incidence, whereas men exhibited higher mortality rates, particularly those with comorbidities such as hypertension and diabetes. High-risk clusters were identified in specific municipalities, including Campo Novo do Parecis, Porto Estrela, and Nova Ubiratã, highlighting the pandemic spatial dynamics within the state. Beyond the acute manifestations of the disease, a growing body of evidence highlights the emergence of post-COVID-19 syndrome, characterized by persistent signs and symptoms lasting more than 90 days after clinical recovery. This study investigated the epidemiological and clinical profiles of individuals who had recovered from COVID-19 in four municipalities of the Vale do São Lourenço region, Mato Grosso, Brazil: Jaciara, Dom Aquino, São Pedro da Cipa, and Juscimeira. These municipalities form a significant demographic and geographic cluster, enabling a robust cross-sectional analysis. A sample of 361 adults who had recovered from COVID-19 underwent clinical evaluations between 3 months and 3 years post-recovery. Majority of participants were female (62.1%), of mixed ethnicity/color (64.82%), and had an average age of approximately 42 years. Most participants completed high school (52.34%) and had an income of up to two minimum wages (66%). The severity of acute disease episode was classified as mild (n=295), moderate (n=52), and critical (n=14). Key findings revealed significant associations between certain behaviors and health conditions, such as physical inactivity, insomnia, smoking, and hypertension—and the severity of acute COVID-19 . A total of 33 persistent symptoms were identified among participants, including fatigue (n=232), headache (n=161), memory loss (n=148), and muscle weakness (n=121). Notably, individuals evaluated more than 12 months post-recovery reported on average, fewer symptoms (6.43) compared to those assessed earlier (7.92). Fatigue persisted across all acute disease severity levels, whereas shortness of breath was predominantly associated with critical cases. Another focus of the study was the gestational and neonatal outcomes among 28 pregnant women infected with SARS-CoV-2. Overall, no severe case requiring hospitalization was recorded; neonatal outcomes were positive, with APGAR scores ranging between 7 and 10 in the first and fifth minutes of life. These results were attributed to the vaccination prioritization of pregnant women, reduzing disease severity in this risk group. This study underscores the importance of integrating clinical, epidemiological, and spatial data to inform public health policies. The findings not only shed light on the long-term impacts of COVID-19 but also emphasize the need for multidisciplinary approaches to address post-COVID-19 syndrome and mitigate future health crises. Public health strategists can leverage these insights to develop targeted interventions, optimize resource allocation, and effectively support vulnerable populations.