OBJECTIVE: With a descriptive epidemiological framing, we assessed whether recent historical patterns of regional influenza burden are reflected in the observed heterogeneity in COVID-19 cases across regions of the world.
METHODS: Weekly surveillance data reported by the World Health Organization from January 2017 to December 2019 for influenza and from January 1, 2020 through October 31, 2020, for COVID-19 were used to assess seasonal and temporal trends for influenza and COVID-19 cases across the seven World Bank regions.
RESULTS: In regions with more pronounced influenza seasonality, COVID-19 epidemics have largely followed trends similar to those seen for influenza from 2017 to 2019. COVID-19 epidemics in countries across Europe, Central Asia, and North America have been marked by a first peak during the spring, followed by significant reductions in COVID-19 cases in the summer months and a second wave in the fall. In Latin America and the Caribbean, COVID-19 epidemics in several countries peaked in the summer, corresponding to months with the highest influenza activity in the region. Countries from regions with less pronounced influenza activity, including South Asia and sub-Saharan Africa, showed more heterogeneity in COVID-19 epidemics seen to date. However, similarities in COVID-19 and influenza trends were evident within select countries irrespective of region.
CONCLUSIONS: Ecological consistency in COVID-19 trends seen to date with influenza trends suggests the potential for shared individual, structural, and environmental determinants of transmission. Using a descriptive epidemiological framework to assess shared regional trends for rapidly emerging respiratory pathogens with better studied respiratory infections may provide further insights into the differential impacts of nonpharmacologic interventions and intersections with environmental conditions. Ultimately, forecasting trends and informing interventions for novel respiratory pathogens like COVID-19 should leverage epidemiologic patterns in the relative burden of past respiratory pathogens as prior information.
METHODS: Based on health stock data from 1990 to 2015 for 140 countries, we estimated Gini coefficients of health stock to investigate associations with a well-known economic flow indicator, Gross Domestic Product (GDP), stock-based national wealth indicator, Inclusive Wealth Index (IWI), and firm-level net income.
RESULTS: The estimated Gini coefficient of global health stock shows that health stock has experienced a global decline. The Gini coefficient for low-income countries (LICs) showed the fastest decline in health stock, dropping from 0.69 to 0.66 in 25 years. Next, rapid population growth and the rise in the youth share of the working-age population in LICs were most likely contributing factors to the decline in inequality. Most countries that experienced positive health stock growth also indicated a strong positive relationship with GDP and IWI. However, some countries showed a negative relationship with natural capital, which is a part of IWI. In addition, firm-level net income showed no obvious associations with health stock, GDP and IWI.
CONCLUSIONS: We argue that a negative relationship between health stock and natural capital is a sign of unstable development because sustainable development involves maintaining not only GDP but also IWI, as it is a collective set of assets or wealth comprising human, produced and natural capital. Moreover, in our analysis of firm-level income data, we also discuss that income will be influenced by other factors, such as innovations, human resources, organization culture and strategy. Therefore, the paper concludes that health stock is a vital component in measuring health inequality and health-related Sustainable Development Goals (SDGs). Thus, IWI is more comprehensive in measuring national wealth and can complement GDP in measuring progress toward sustainable development.
METHODS: We downloaded COVID-19 outbreak data of the number of confirmed cases in all countries as of October 19, 2020. The IRT-based predictive model was built to determine the pandemic IP for each country. A model building scheme was demonstrated to fit the number of cumulative infected cases. Model parameters were estimated using the Solver add-in tool in Microsoft Excel. The absolute advantage coefficient (AAC) was computed to track the IP at the minimum of incremental points on a given ogive curve. The time-to-event analysis (a.k.a. survival analysis) was performed to compare the difference in IPs among continents using the area under the curve (AUC) and the respective 95% confidence intervals (CIs). An online comparative dashboard was created on Google Maps to present the epidemic prediction for each country.
RESULTS: The top 3 countries that were hit severely by COVID-19 were France, Malaysia, and Nepal, with IP days at 263, 262, and 262, respectively. The top 3 continents that were hit most based on IP days were Europe, South America, and North America, with their AUCs and 95% CIs at 0.73 (0.61-0.86), 0.58 (0.31-0.84), and 0.54 (0.44-0.64), respectively. An online time-event result was demonstrated and shown on Google Maps, comparing the IP probabilities across continents.
CONCLUSION: An IRT modeling scheme fitting the epidemic data was used to predict the length of IP days. Europe, particularly France, was hit seriously by COVID-19 based on the IP days. The IRT model incorporated with AAC is recommended to determine the pandemic IP.
METHODS: This study was conducted based on the PRISMA 2020 criteria. Initial searching was conducted using MeSH (Medical Subject Headings)-based keywords with no time limitation (by August 1, 2024). Collected papers were transferred to Citation Management Software (EndNote). Duplicate studies were merged and primary and secondary screenings were applied based on the inclusion/exclusion criteria. Validation was considered to find high-quality assessments. Finally, eligible extractable papers were enrolled for data collection. Data was analyzed using Comprehensive Meta-Analysis software (v.2) The random effects model was used in case of I2 index above 50%.In order to investigate the factors affecting the heterogeneity of studies, meta-regression tests were used to examine factors such as sample size and year of study.
RESULTS: One hundred thirty-eight eligible studies with a total sample size of 135,098 pregnant women individuals were selected for data extraction and analysis. The heterogeneity index was found high (I2:98.9) and the random effect model was used for analysis. The egger test revealed the absence of publication bias in collected studies (p:0.088). Thus, the global seroprevalence of Toxoplasma gondii in pregnant women was reported at 36.6% (95%CI:33.7-39.6). the highest prevalence reported based on meta-analysis was reported in South America with 52.8% (95% CI:46.6-59), while only 15 studies were reviewed in this continent, most of which were in Brazil. Therefore, after the continent, the highest prevalence reported was reported in Africa with 46.8% (95% CI:39.5-54.3). Also, the lowest prevalence reported based on meta-analysis was in North America with 19.7% (95% CI:8.4-39.6) and Europe with 24.6% (95% CI:17.8-32.9).
CONCLUSION: This study revealed a high level of seroprevalence of Toxoplasma gondii in pregnant women worldwide. This value mostly depends on the individual's age, lifestyle, and disease awareness regarding toxoplasmosis in pregnant women. Thus, public awareness, along with comprehensive health programs regarding the detrimental effects of toxoplasmosis in pregnant women, seems necessary for prevention or even early diagnosis of toxoplasmosis in pregnant women.
DESIGN: Cross-sectional survey.
SETTING: Community.
PARTICIPANTS: People of employable age (N=9875; 18-64 y) with traumatic or non-traumatic SCI (including cauda equina syndrome) who were at least 18 years of age at the time of the survey, living in the community, and able to respond to one of the available language versions of the questionnaire.
INTERVENTIONS: Not applicable MAIN OUTCOME MEASURES: The observed employment rate was defined as performing paid work for at least 1 hour a week, and predicted employment rate was adjusted for sample composition from mixed logistic regression analysis.
RESULTS: A total of 9875 participants were included (165-1174 per country). Considerable differences in sample composition were found. The observed worldwide employment rate was 38%. A wide variation was found across countries, ranging from 10.3% to 61.4%. Some countries showed substantially higher or lower employment rates than predicted based on the composition of their sample. Gaps between the observed employment rates among participants with SCI and the general population ranged from 14.8% to 54.8%. On average, employment rates were slightly higher among men compared with women, but with large variation across countries. Employment gaps, however, were smaller among women for most countries.
CONCLUSIONS: This first worldwide survey among people with SCI shows an average employment rate of 38%. Differences between observed and predicted employment rates across countries point at country-specific factors that warrant further investigation. Gaps with employment rates in the general population were considerable and call for actions for more inclusive labor market policies in most of the countries investigated.
METHODS: Data from World Health Survey conducted in 2002-2004 in low-middle- and high-income countries were used. Participants aged 18 years and over were selected using multistage, stratified cluster sampling. BMI was used as an outcome variable. Culture of the countries was measured using Hofstede's cultural dimensions: Uncertainty avoidance, individualism, Power Distance and masculinity. The potential determinants of individual-level BMI were participants' sex, age, marital status, education, occupation as well as household-wealth and location (rural/urban) at the individual-level. The country-level factors used were average national income (GNI-PPP), income inequality (Gini-index) and Hofstede's cultural dimensions. A two-level random-intercepts and fixed-slopes model structure with individuals nested within countries were fitted, treating BMI as a continuous outcome variable.
RESULTS: A sample of 156,192 people from 53 countries was included in this analysis. The design-based (weighted) mean BMI (SE) in these 53 countries was 23.95(0.08). Uncertainty avoidance (UAI) and individualism (IDV) were significantly associated with BMI, showing that people in more individualistic or high uncertainty avoidance countries had higher BMI than collectivist or low uncertainty avoidance ones. This model explained that one unit increase in UAI or IDV was associated with 0.03 unit increase in BMI. Power distance and masculinity were not associated with BMI of the people. National level Income was also significantly associated with individual-level BMI.
CONCLUSION: National culture has a substantial association with BMI of the individuals in the country. This association is important for understanding the pattern of obesity or overweight across different cultures and countries. It is also important to recognise the importance of the association of culture and BMI in developing public health interventions to reduce obesity or overweight.
SUMMARY: This study examined country-specific prevalence and incidence data of youth-onset T2D published between 2008 and 2019, and searched for national guidelines to expand the understanding of country-specific similarities and differences. Of the 1,190 articles and 17 congress abstracts identified, 58 were included in this review. Our search found the highest reported prevalence rates of youth-onset T2D in China (520 cases/100,000 people) and the USA (212 cases/100,000) and lowest in Denmark (0.6 cases/100,000) and Ireland (1.2 cases/100,000). However, the highest incidence rates were reported in Taiwan (63 cases/100,000) and the UK (33.2 cases/100,000), with the lowest in Fiji (0.43 cases/100,000) and Austria (0.6 cases/100,000). These differences in epidemiology data may be partly explained by variations in the diagnostic criteria used within studies, screening recommendations within national guidelines and race/ethnicity within countries. Key Messages: Our study suggests that published country-specific epidemiology data for youth-onset T2D are varied and scant, and often with reporting inconsistencies. Finding optimal diagnostic criteria and screening strategies for this disease should be of high interest to every country.
TRIAL REGISTRATION: Not applicable.
OBJECTIVES: We aimed to examine the extent and identify factors associated with psychological distress, fear of COVID-19 and coping.
METHODS: We conducted a cross-sectional study across 17 countries during Jun-2020 to Jan-2021. Levels of psychological distress (Kessler Psychological Distress Scale), fear of COVID-19 (Fear of COVID-19 Scale), and coping (Brief Resilient Coping Scale) were assessed.
RESULTS: A total of 8,559 people participated; mean age (±SD) was 33(±13) years, 64% were females and 40% self-identified as frontline workers. More than two-thirds (69%) experienced moderate-to-very high levels of psychological distress, which was 46% in Thailand and 91% in Egypt. A quarter (24%) had high levels of fear of COVID-19, which was as low as 9% in Libya and as high as 38% in Bangladesh. More than half (57%) exhibited medium to high resilient coping; the lowest prevalence (3%) was reported in Australia and the highest (72%) in Syria. Being female (AOR 1.31 [95% CIs 1.09-1.57]), perceived distress due to change of employment status (1.56 [1.29-1.90]), comorbidity with mental health conditions (3.02 [1.20-7.60]) were associated with higher levels of psychological distress and fear. Doctors had higher psychological distress (1.43 [1.04-1.97]), but low levels of fear of COVID-19 (0.55 [0.41-0.76]); nurses had medium to high resilient coping (1.30 [1.03-1.65]).
CONCLUSIONS: The extent of psychological distress, fear of COVID-19 and coping varied by country; however, we identified few higher risk groups who were more vulnerable than others. There is an urgent need to prioritise health and well-being of those people through well-designed intervention that may need to be tailored to meet country specific requirements.
METHODS: We assembled 1155 geographical records of yellow fever virus infection in people from 1970 to 2016. We used a Poisson point process boosted regression tree model that explicitly incorporated environmental and biological explanatory covariates, vaccination coverage, and spatial variability in disease reporting rates to predict the relative risk of apparent yellow fever virus infection at a 5 × 5 km resolution across all risk zones (47 countries across the Americas and Africa). We also used the fitted model to predict the receptivity of areas outside at-risk zones to the introduction or reintroduction of yellow fever transmission. By use of previously published estimates of annual national case numbers, we used the model to map subnational variation in incidence of yellow fever across at-risk countries and to estimate the number of cases averted by vaccination worldwide.
FINDINGS: Substantial international and subnational spatial variation exists in relative risk and incidence of yellow fever as well as varied success of vaccination in reducing incidence in several high-risk regions, including Brazil, Cameroon, and Togo. Areas with the highest predicted average annual case numbers include large parts of Nigeria, the Democratic Republic of the Congo, and South Sudan, where vaccination coverage in 2016 was estimated to be substantially less than the recommended threshold to prevent outbreaks. Overall, we estimated that vaccination coverage levels achieved by 2016 avert between 94 336 and 118 500 cases of yellow fever annually within risk zones, on the basis of conservative and optimistic vaccination scenarios. The areas outside at-risk regions with predicted high receptivity to yellow fever transmission (eg, parts of Malaysia, Indonesia, and Thailand) were less extensive than the distribution of the main urban vector, A aegypti, with low receptivity to yellow fever transmission in southern China, where A aegypti is known to occur.
INTERPRETATION: Our results provide the evidence base for targeting vaccination campaigns within risk zones, as well as emphasising their high effectiveness. Our study highlights areas where public health authorities should be most vigilant for potential spread or importation events.
FUNDING: Bill & Melinda Gates Foundation.
METHODS: Drowning mortality data of 61 countries were extracted from the World Health Organization Mortality Database. We calculated the percentage change (PC) in age-standardized drowning mortality rates and percentage of drowning deaths reported with unspecified codes between 2004 and 2005 and 2014-2015.
RESULTS: Of the 61 countries studied, 50 exhibited a reduction in drowning mortality rates from 2004 to 2005 to 2014-2015. Additionally, five countries-Lithuania, Moldova, Kyrgyzstan, Romania, and El Salvador-with a high mortality rate in 2004-2005 (> 40 deaths per 100,000) showed improvement (PC 40%) exhibited a marked reduction (PC
METHODS: The D-PRISM study was a multinational, survey-based investigation to assess the diagnosis and treatment of pneumonia in the ICU. A self-administered online questionnaire was distributed to intensive care clinicians from 72 countries between September to November 2022. The questionnaire included sections on professional profiles, current clinical practice in diagnosing and managing CAP, HAP, and VAP, and the availability of microbiology diagnostic tests. Multivariable analysis using multiple regression analysis was used to assess the relationship between reported antibiotic duration and organisational variables collected in the study.
RESULTS: A total of 1296 valid responses were collected from ICU clinicians, spread between low-and-middle income (LMIC) and high-income countries (HIC), with LMIC respondents comprising 51% of respondents. There is heterogeneity across the diagnostic processes, including clinical assessment, where 30% (389) did not consider radiological evidence essential to diagnose pneumonia, variable collection of microbiological samples, and use and practice in bronchoscopy. Microbiological diagnostics were least frequently available in low and lower-middle-income nation settings. Modal intended antibiotic treatment duration was 5-7 days for all types of pneumonia. Shorter durations of antibiotic treatment were associated with antimicrobial stewardship (AMS) programs, high national income status, and formal intensive care training.
CONCLUSIONS: This study highlighted variations in clinical practice and diagnostic capabilities for pneumonia, particularly issues with access to diagnostic tools in LMICs were identified. There is a clear need for improved adherence to existing guidelines and standardized approaches to diagnosing and treating pneumonia in the ICU. Trial registration As a survey of current practice, this study was not registered. It was reviewed and endorsed by the European Society of Intensive Care Medicine.