Global Health Epidemiology and Disease Control

Stroke is the second leading cause of death and disability in Latin America; however, few epidemiological studies have been conducted in South America. An observational study was conducted to analyze trends in stroke mortality in South American (SA) countries. Age-standardized mortality rates and proportional mortality due to stroke in the populations of SA countries between 1990 and 2019 were assessed by extracting data from the Global Burden of Disease 2019 study. Joinpoint regression models were employed to identify trends in the annual percentage change in mortality rates for each segment. Considering the data collected over the 30 years that were studied, the age-standardized stroke mortality trend decreased in Argentina (−1.6%), Uruguay (−0.6%), Brazil (−0.5%), Guyana (−0.5%), and Bolivia (−0.4%), while Venezuela (+1.6%) and Suriname (+1.0%) showed an increasing trend. The proportional stroke mortality trend decreased in Argentina (−1.7%), Paraguay (−0.9%), Uruguay (−0.7%), Guyana (−0.7%), Brazil (−0.5%), and Chile (−0.5%), whereas Bolivia (+1.0%), Suriname (+0.6%), and Peru (+0.4%) exhibited an increasing trend. The trends in stroke mortality between 1990 and 2019 demonstrated considerable variability. While most SA countries experienced significant decreases in stroke mortality trends, Venezuela and Suriname showed increases in age-standardized mortality rates, and Bolivia, Suriname, and Peru exhibited increases in proportional mortality rates. No decreasing stroke mortality trend was observed in the segment after the last joinpoint, highlighting the need for improvement in prevention and treatment. Full article

Over one million Syrian refugees have been residing in substandard living conditions in Lebanon for the past decade. Non-invasive biomonitoring of fractional exhaled nitric oxide (FeNO) as a pulmonary inflammation biomarker was conducted following and preceding indoor environmental assessments (which revealed elevated mould counts in informal tented settlements and non-residential shelters) to further evaluate effects of environmental exposure to indoor contaminants. Results of biomonitoring (n = 57) provided some insight regarding existing respiratory conditions and the possible implementation of minimally invasive methods to establish susceptibility profiles in Syrian refugees amid limited access to healthcare. The clinical interpretation of FeNO results suggested possible persistent exposure to allergens in addition to significant type 2 inflammation in some subjects. These findings warrant the need to expand this study, investigate other biomarkers, and attempt to correlate findings with environmental conditions to evaluate if a dose–response relationship exists. Full article

The north region of Brazil is characterized by significant vulnerabilities, notably surpassing national poverty indicators. These disparities exacerbated the impact of respiratory illnesses on the healthcare system during the COVID-19 pandemic, particularly in areas with limited healthcare resources, inadequate infrastructure, and barriers to healthcare access. The crisis was further influenced by multiple lineages that emerged as significant virus variants associated with increased transmissibility. Within this context, our ecological study focused on analyzing the epidemiological evolution of COVID-19 in the state of Acre. We constructed time-series trends in incidence, lethality, and mortality from March 2020 to December 2022 using the Prais–Winsten regression model. Our findings revealed that in 2020, there was an increasing trend in incidence, while mortality and lethality continued to decrease (p < 0.05). In the following year, both incidence and mortality decreased, while lethality increased at a rate of 1.02% per day. By the end of 2022, trends remained stationary across all rates. These results underscore the importance of ongoing surveillance and adaptive public health measures to bolster the resilience of healthcare systems in remote and vulnerable regions. Indeed, continuous monitoring of the most predominant SARS-CoV-2 lineages and their dynamics is imperative. Such proactive actions are essential for addressing emerging challenges and ensuring effective responses to adverse situations. Full article

HIV/AIDS has been a major threat to global public health, with India ranking third when it comes to the global burden of people living with HIV, especially women. It is imperative to assess the level of knowledge women have about transmission and prevention of this infection. This study sought to delineate the determinants of the comprehensive knowledge of HIV/AIDS among women in the reproductive age groups in India. Data from the fifth round of the National Family Health Survey conducted in India were analyzed. The sample included 95,541 women aged 15–49 years. Multilevel logistic regression was fitted with individual characteristics, household characteristics, and community characteristics to identify determinants of comprehensive knowledge on HIV/AIDS. Nearly a fourth (24.8%) of the women aged 15–49 in India who had ever heard of HIV had comprehensive knowledge of HIV/AIDS. Multilevel logistic regression showed that the likelihood of comprehensive knowledge of HIV/AIDS was higher among women aged 40–44 (AOR = 1.57) and 30–34 (AOR = 1.56). The likelihood of having comprehensive knowledge increased with the increase in the level of education. Women with secondary and higher levels of education were 1.9 times and 3.38 times more likely to have comprehensive knowledge, respectively, than those with no education. Household wealth, access to mass media, and having ever tested for HIV were also significant determinants of comprehensive knowledge of HIV/AIDS among women. The odds of having comprehensive knowledge about HIV/AIDS were higher for women with higher community wealth (AOR = 1.31), higher community education (AOR = 1.09), and higher community employment (AOR = 1.12). Factors at both the individual and community levels were shown to be indicators of comprehensive knowledge of HIV/AIDS. Policymakers and public health practitioners in India should come up with plans to close the information gaps about HIV/AIDS that exist among women and their demographic subgroups. Full article

Infectious disease epidemics are challenging for medical and public health practitioners. They require prompt treatment, but it is challenging to recognize and define epidemics in real time. Knowing the prediction of an infectious disease epidemic can evaluate and prevent the disease’s impact. Mathematical models of epidemics that work in real time are important tools for preventing disease, and data-driven deep learning enables practical algorithms for identifying parameters in mathematical models. In this paper, the SIR model was reduced to a logistic differential equation involving a constant parameter and a time-dependent function. The time-dependent function leads to constant, rational, and birational models. These models use several constant parameters from the available data to predict the time and number of people reported to be infected with the COVID-19 Omicron variant. Two out of these three models, rational and birational, provide accurate predictions for countries that practice strict mitigation measures, but fail to provide accurate predictions for countries that practice partial mitigation measures. Therefore, we introduce a time-series model based on neural networks to predict the time and number of people reported to be infected with the COVID-19 Omicron variant in a given country that practices both partial and strict mitigation measures. A logistics-informed neural network algorithm was also introduced. This algorithm takes as input the daily and cumulative number of people who are reported to be infected with the COVID-19 Omicron variant in the given country. The algorithm helps determine the analytical solution involving several constant parameters for each model from the available data. The accuracy of these models is demonstrated using error metrics on Omicron variant data for Portugal, Italy, and China. Our findings demonstrate that the constant model could not accurately predict the daily or cumulative infections of the COVID-19 Omicron variant in the observed country because of the long series of existing data of the epidemics. However, the rational and birational models accurately predicted cumulative infections in countries adopting strict mitigation measures, but they fell short in predicting the daily infections. Furthermore, both models performed poorly in countries with partial mitigation measures. Notably, the time-series model stood out for its versatility, effectively predicting both daily and cumulative infections in countries irrespective of the stringency of their mitigation measures. Full article

An increasing base of evidence suggests that respiratory syncytial virus (RSV) infections may be associated with neurological complications. In accord with the PRISMA statement, we performed a systematic review and meta-analysis on the occurrence of encephalitis and encephalopathy associated with documented RSV infections. PubMed, Embase, and Scopus databases were searched for eligible observational studies published up to 10 April 2024. Raw data included the occurrence of RSV infections among cases of encephalitis and/or encephalopathy and cases of encephalitis and/or encephalopathy among series of RSV infections. Data were pooled in a random effects model. Case reports were also collected, and their data pooled as a cumulative series. Heterogeneity was assessed using the I² measure, while reporting bias was assessed by means of funnel plots and regression analysis. A total of 15 studies for a total of 7719 RSV infections and 1631 cases of encephalitis were analyzed. Moreover, 27 case reports and case series were retrieved, for a total of 84 individual cases of encephalitis/encephalopathy occurring during a documented RSV infection. A pooled prevalence of 2.20 cases of encephalitis/encephalopathy per 100 RSV cases (I² = 99%) was calculated, while a prevalence of RSV infections among cases of encephalitis/encephalopathy was estimated to 3.53 per 100 cases for studies on respiratory specimens (I² = 48%) and 0.37 per cases on central nervous system (CNS) specimens (I² = 0%). Detection of RSV within the CNS was relatively rare (17.86% of pooled case reports), being associated with male gender (adjusted odds ratio [aOR] 5.021, 95% confidence interval [95%CI] 1.104 to 22.831) and recovery with long-term sequelae (aOR 5.699, 95%CI 1.152; 28.183). Case fatality ratio was estimated to be 0.43 per 100 cases on observational studies and 10.71% in case reports, a difference likely due to publication bias. In summary, RSV represented a not frequent but notable cause of encephalitis/encephalopathy in adults and children. The paucity of available studies not only recommends a cautious appraisal of our results but stresses the clinical significance of future studies on incident cases of encephalitis and/or encephalopathy. Full article

Respiratory diseases, including respiratory syncytial virus (RSV) infections, are common reasons for seeking healthcare among refugees and asylum seekers. A systematic review with meta-analysis was designed to appraise all the available evidence on RSV infections among individuals in refugee camps. Three medical databases (PubMed, Embase, and Scopus) as well as the preprint repository medRxiv.org were searched for eligible observational studies, and the collected cases were pooled in a random-effects meta-analysis model. Heterogeneity was assessed using the I² statistics. Funnel plots and a regression analysis were calculated for analyzing reporting bias. Eventually, six studies were retrieved from three areas (Bangladesh, Thailand, and Kenya), with pooled estimates of 129.704 cases per 1000 samples (95% CI 66.393 to 237.986) for RSV compared to 110.287 per 1000 people for influenza A (95% CI 73.186 to 162.889), 136.398 cases per 1000 people (95% CI 84.510 to 212.741) for human adenovirus (HAdV), 69.553 per 1000 people (95% CI 49.802 to 96.343) for parainfluenzavirus (PIFV), and 60.338 per 1000 people (95% CI 31.933 to 111.109) for human metapneumovirus (hMPV). Using influenza A as a reference group, the risk for a positive specimen was greater for RSV (relative risk [RR] 1.514, 95% CI 1.396 to 1.641) and HAdV (RR 1.984, 95% CI 1.834 to 2.146) and lower for influenza B (RR 0.276, 95% CI: 0.239 to 0.319), PIFV (RR: 0.889, 95% CI 0.806 to 0.981), and hMPV (RR 0.594, 95% CI 0.534 to 0.662). In summary, high rates of RSV infections were documented among individuals sheltered in refugee camps, stressing the importance of specifically designed preventive strategies. Full article

Theories of myopia etiology based on near work and lack of outdoor exposure have had inconsistent support and have not prevented the rising prevalence of global myopia. New scientific theories in the cause and prevention of myopia are needed. Myopia prevalence is low in native people consuming traditional diets lacking in sodium chloride, and nutritional epidemiological evidence supports the association of rising myopia prevalence with dietary sodium intake. East Asian populations have among the highest rates of myopia associated with high dietary sodium. Similar associations of sodium and rising myopia prevalence were observed in the United States in the late 20th century. The present perspective synthesizes nutritional epidemiology evidence with pathophysiological concepts and proposes that axial myopia occurs from increased fluid retention in the vitreous of the eye, induced by dietary sodium chloride intake. Salt disturbs ionic permeability of retinal membranes, increases the osmotic gradient flow of fluid into the vitreous, and stretches ocular tissue during axial elongation. Based on the present nutritional epidemiology evidence, experimental research should investigate the effect of sodium chloride as the cause of myopia, and clinical research should test a very low-salt diet in myopia correction and prevention. Full article