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1.
Medicine (Baltimore) ; 100(21): e25645, 2021 May 28.
Article in English | MEDLINE | ID: covidwho-2190994

ABSTRACT

ABSTRACT: Since December 2019, pneumonia caused by a novel coronavirus (SARS-CoV-2), namely 2019 novel coronavirus disease (COVID-19), has rapidly spread from Wuhan city to other cities across China. The present study was designed to describe the epidemiology, clinical characteristics, treatment, and prognosis of 74 hospitalized patients with COVID-19.Clinical data of 74 COVID-19 patients were collected to analyze the epidemiological, demographic, laboratory, radiological, and treatment data. Thirty-two patients were followed up and tested for the presence of the viral nucleic acid and by pulmonary computed tomography (CT) scan at 7 and 14 days after they were discharged.Among all COVID-19 patients, the median incubation period for patients and the median period from symptom onset to admission was all 6 days; the median length of hospitalization was 13 days. Fever symptoms were presented in 83.78% of the patients, and the second most common symptom was cough (74.32%), followed by fatigue and expectoration (27.03%). Inflammatory indicators, erythrocyte sedimentation rate (ESR), and C-reactive protein (CRP) of the intensive care unit (ICU) patients were significantly higher than that of the non-ICU patients (P < .05). However, 50.00% of the ICU patients had their the ratio of T helper cells to cytotoxic T cells (CD4/CD8) ratio lower than 1.1, whose proportion is much higher than that in non-ICU patients (P < .01).Compared with patients in Wuhan, COVID-19 patients in Anhui Province seemed to have milder symptoms of infection, suggesting that there may be some regional differences in the transmission of SARS-CoV-2 between different cities.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19/diagnosis , Cough/epidemiology , Fever/epidemiology , Hyperbaric Oxygenation/statistics & numerical data , Adolescent , Adult , Aged , Antibiotic Prophylaxis/statistics & numerical data , Blood Sedimentation , C-Reactive Protein/analysis , COVID-19/complications , COVID-19/epidemiology , COVID-19/therapy , COVID-19 Nucleic Acid Testing , Child , Child, Preschool , China/epidemiology , Cities/epidemiology , Cough/blood , Cough/therapy , Cough/virology , Female , Fever/blood , Fever/therapy , Fever/virology , Follow-Up Studies , Geography , Humans , Length of Stay/statistics & numerical data , Lung/diagnostic imaging , Male , Middle Aged , RNA, Viral/isolation & purification , Retrospective Studies , SARS-CoV-2/genetics , SARS-CoV-2/isolation & purification , Severity of Illness Index , Tomography, X-Ray Computed , Young Adult
2.
BMJ Open ; 12(11): e065709, 2022 11 01.
Article in English | MEDLINE | ID: covidwho-2097998

ABSTRACT

OBJECTIVES: The association between impaired digital provision, access and health outcomes has not been systematically studied. The Wolverhampton Digital ENablement programme (WODEN) is a multiagency collaborative approach to determine and address digital factors that may impact on health and social care in a single deprived multiethnic health economy. The objective of this study is to determine the association between measurable broadband provision and demographic and health outcomes in a defined population. DESIGN: An observational cross-sectional whole local population-level study with cohorts defined according to broadband provision. SETTING/PARTICIPANTS: Data for all residents of the City of Wolverhampton, totalling 269 785 residents. PRIMARY OUTCOMES: Poor broadband provision is associated with variation in demographics and with increased comorbidity and urgent care needs. RESULTS: Broadband provision was measured using the Broadband Infrastructure Index (BII) in 158 City localities housing a total of 269 785 residents. Lower broadband provision as determined by BII was associated with younger age (p<0.001), white ethnic status (p<0.001), lesser deprivation as measured by Index of Multiple Deprivation (p<0.001), a higher number of health comorbidities (p<0.001) and more non-elective urgent events over 12 months (p<0.001). CONCLUSION: Local municipal and health authorities are advised to consider the variations in broadband provision within their locality and determine equal distribution both on a geographical basis but also against demographic, health and social data to determine equitable distribution as a platform for equitable access to digital resources for their residents.


Subject(s)
Economics, Medical , Ethnicity , Humans , Cross-Sectional Studies , Geography , Social Support
3.
Infect Control Hosp Epidemiol ; 42(2): 240-242, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-2096317
4.
PLoS One ; 17(10): e0276267, 2022.
Article in English | MEDLINE | ID: covidwho-2079763

ABSTRACT

Many university-taught courses moved to online form since the outbreak of the global pandemic of coronavirus disease (COVID-19). Distance learning has become broadly used as a result of the widely applied lockdowns, however, many students lack personal contact in the learning process. A classical web-based distance learning does not provide means for natural interpersonal interaction. The technology of immersive virtual reality (iVR) may mitigate this problem. Current research has been aimed mainly at specific instances of collaborative immersive virtual environment (CIVE) applications for learning. The fields utilizing iVR for knowledge construction and skills training with the use of spatial visualizations show promising results. The objective of this study was to assess the effectiveness of collaborative and individual use of iVR for learning geography, specifically training in hypsography. Furthermore, the study's goals were to determine whether collaborative learning would be more effective and to investigate the key elements in which collaborative and individual learning were expected to differ-motivation and use of cognitive resources. The CIVE application developed at Masaryk University was utilized to train 80 participants in inferring conclusions from cartographic visualizations. The collaborative and individual experimental group underwent a research procedure consisting of a pretest, training in iVR, posttest, and questionnaires. A statistical comparison between the geography pretest and posttest for the individual learning showed a significant increase in the score (p = 0.024, ES = 0.128) and speed (p = 0.027, ES = 0.123), while for the collaborative learning, there was a significant increase in the score (p<0.001, ES = 0.333) but not in speed (p = 1.000, ES = 0.000). Thus, iVR as a medium proved to be an effective tool for learning geography. However, comparing the collaborative and individual learning showed no significant difference in the learning gain (p = 0.303, ES = 0.115), speed gain (p = 0.098, ES = 0.185), or performance motivation (p = 0.368, ES = 0.101). Nevertheless, the collaborative learning group had significantly higher use of cognitive resources (p = 0.046, ES = 0.223) than the individual learning group. The results were discussed in relation to the cognitive load theories, and future research directions for iVR learning were proposed.


Subject(s)
COVID-19 , Virtual Reality , Humans , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control , Learning , Geography
5.
Vox Sang ; 116(2): 155-166, 2021 Feb.
Article in English | MEDLINE | ID: covidwho-2078680

ABSTRACT

BACKGROUND AND OBJECTIVE: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is a novel coronavirus, first identified in China at the end of 2019 and has now caused a worldwide pandemic. In this review, we provide an overview of the implications of SARS-CoV-2 for blood safety and sufficiency. MATERIAL AND METHOD: We searched the PubMed database, the preprint sites bioRxiv and medRxiv, the websites of the World Health Organization, European Centre for Disease Prevention and Control, the US Communicable Diseases Center and monitored ProMed updates. RESULTS: An estimated 15%-46% of SARS-CoV-2 infections are asymptomatic. The reported mean incubation period is 3 to 7 days with a range of 1-14 days. The blood phase of SARS-CoV-2 appears to be brief and low level, with RNAaemia detectable in only a small proportion of patients, typically associated with more severe disease and not demonstrated to be infectious virus. An asymptomatic blood phase has not been demonstrated. Given these characteristics of SARS-CoV-2 infection and the absence of reported transfusion transmission (TT), the TT risk is currently theoretical. To mitigate any potential TT risk, but more importantly to prevent respiratory transmission in donor centres, blood centres can implement donor deferral policies based on travel, disease status or potential risk of exposure. CONCLUSION: The TT risk of SARS-CoV-2 appears to be low. The biggest risk to blood services in the current COVID-19 pandemic is to maintain the sufficiency of the blood supply while minimizing respiratory transmission of SARS-CoV-19 to donors and staff while donating blood.


Subject(s)
Blood Safety , COVID-19/blood , COVID-19/prevention & control , COVID-19/virology , Transfusion Reaction/prevention & control , Blood Transfusion , Geography , Humans , RNA, Viral/analysis , Risk Assessment , SARS-CoV-2 , Safety Management , World Health Organization
7.
Proc Natl Acad Sci U S A ; 119(35): e2122851119, 2022 08 30.
Article in English | MEDLINE | ID: covidwho-2001002

ABSTRACT

Disease transmission prediction across wildlife is crucial for risk assessment of emerging infectious diseases. Susceptibility of host species to pathogens is influenced by the geographic, environmental, and phylogenetic context of the specific system under study. We used machine learning to analyze how such variables influence pathogen incidence for multihost pathogen assemblages, including one of direct transmission (coronaviruses and bats) and two vector-borne systems (West Nile Virus [WNV] and birds, and malaria and birds). Here we show that this methodology is able to provide reliable global spatial susceptibility predictions for the studied host-pathogen systems, even when using a small amount of incidence information (i.e., [Formula: see text] of information in a database). We found that avian malaria was mostly affected by environmental factors and by an interaction between phylogeny and geography, and WNV susceptibility was mostly influenced by phylogeny and by the interaction between geographic and environmental distances, whereas coronavirus susceptibility was mostly affected by geography. This approach will help to direct surveillance and field efforts providing cost-effective decisions on where to invest limited resources.


Subject(s)
Animals, Wild , Communicable Diseases, Emerging , Disease Susceptibility , Animals , Animals, Wild/parasitology , Animals, Wild/virology , Bird Diseases/epidemiology , Bird Diseases/transmission , Chiroptera/virology , Communicable Diseases, Emerging/epidemiology , Communicable Diseases, Emerging/transmission , Communicable Diseases, Emerging/veterinary , Coronavirus , Coronavirus Infections/epidemiology , Coronavirus Infections/transmission , Coronavirus Infections/veterinary , Databases, Factual , Environment , Epidemiological Monitoring , Geography , Host-Pathogen Interactions , Incidence , Machine Learning , Malaria/epidemiology , Malaria/transmission , Malaria/veterinary , Phylogeny , Risk Assessment , West Nile Fever/epidemiology , West Nile Fever/transmission , West Nile Fever/veterinary , West Nile virus
8.
Proc Natl Acad Sci U S A ; 119(32): e2120025119, 2022 08 09.
Article in English | MEDLINE | ID: covidwho-1972763

ABSTRACT

Hundreds of millions of poor families receive some form of targeted social assistance. Many of these antipoverty programs involve some degree of geographic targeting, where aid is prioritized to the poorest regions of the country. However, policy makers in many low-resource settings lack the disaggregated poverty data required to make effective geographic targeting decisions. Using several independent datasets from Nigeria, this paper shows that high-resolution poverty maps, constructed by applying machine learning algorithms to satellite imagery and other nontraditional geospatial data, can improve the targeting of government cash transfers to poor families. Specifically, we find that geographic targeting relying on machine learning-based poverty maps can reduce errors of exclusion and inclusion relative to geographic targeting based on recent nationally representative survey data. This result holds for antipoverty programs that target both the poor and the extreme poor and for initiatives of varying sizes. We also find no evidence that machine learning-based maps increase targeting disparities by demographic groups, such as gender or religion. Based in part on these findings, the Government of Nigeria used this approach to geographically target emergency cash transfers in response to the COVID-19 pandemic.


Subject(s)
Poverty , Social Welfare , Geography , Humans , Nigeria
9.
Contraception ; 115: 17-21, 2022 11.
Article in English | MEDLINE | ID: covidwho-1966462

ABSTRACT

OBJECTIVES: Prior research identified a significant decline in the number of abortions in Louisiana at the onset of the COVID-19 pandemic, as well as increases in second-trimester abortions and decreases in medication abortions. This study examines how service disruptions in particular areas of the state disparately affected access to abortion care based on geography. STUDY DESIGN: We collected monthly service data from Louisiana's abortion clinics (January 2018-May 2020) and conducted mystery client calls to determine whether clinics were scheduling appointments at pandemic onset (April-May 2020). We used segmented regression to assess whether service disruptions modified the main pandemic effects on the number, timing, and type of abortions using stratified models and interaction terms. Additionally, we calculated the median distance that Louisiana residents traveled to the clinic where they obtained care. RESULTS: For residents whose closest clinic was consistently scheduling appointments at the onset of the pandemic, the number of monthly abortions did not change (IRR = 1.07, 95% CI: 0.84-1.36). For those whose closest clinic services were disrupted, the number of monthly abortions decreased by 46% (IRR = 0.54, 95% CI: 0.45-0.65). Similarly, increases in second-trimester abortions and decreases in medication abortions were concentrated in areas where residents experienced service disruptions (AOR = 2.25, 95% CI: 1.21-4.56 and AOR = 0.59, 95% CI: 0.29-0.87, respectively) and were not seen elsewhere in the state. CONCLUSION: Changes in the number, timing and type of abortions were concentrated among residents in particular areas of Louisiana. The early stages of the COVID-19 pandemic exacerbated geographic disparities in access to abortion care. IMPLICATIONS: Disruptions in services at the beginning of the COVID-19 pandemic in Louisiana meaningfully affected pregnant people's ability to obtain an abortion at their nearest clinic. These findings reinforce the importance of developing mechanisms to support pregnant people during emergency situations when traveling to a nearby clinic is no longer possible.


Subject(s)
Abortion, Induced , COVID-19 , Healthcare Disparities , Pandemics , Abortion, Induced/statistics & numerical data , COVID-19/epidemiology , Female , Geography , Healthcare Disparities/statistics & numerical data , Humans , Louisiana/epidemiology , Pregnancy
10.
Sci Rep ; 12(1): 12781, 2022 07 27.
Article in English | MEDLINE | ID: covidwho-1960507

ABSTRACT

The main targets of this were to screen the factors that may influence the distribution of 25-hydroxyvitamin D[25(OH)D] reference value in healthy elderly people in China, and further explored the geographical distribution differences of 25(OH)D reference value in China. In this study, we collected the 25(OH)D of 25,470 healthy elderly from 58 cities in China to analyze the correlation between 25(OH)D and 22 geography secondary indexes through spearman regression analysis. Six indexes with significant correlation were extracted, and a ridge regression model was built, and the country's urban healthy elderly'25(OH)D reference value was predicted. By using the disjunctive Kriging method, we obtained the geographical distribution of 25(OH)D reference values for healthy elderly people in China. The reference value of 25(OH)D for healthy elderly in China was significantly correlated with the 6 secondary indexes, namely, latitude (°), annual temperature range (°C), annual sunshine hours (h), annual mean temperature (°C), annual mean relative humidity (%), and annual precipitation (mm). The geographical distribution of 25(OH)D values of healthy elderly in China showed a trend of being higher in South China and lower in North China, and higher in coastal areas and lower in inland areas. This study lays a foundation for further research on the mechanism of different influencing factors on the reference value of 25(OH)D index. A ridge regression model composed of significant influencing factors has been established to provide the basis for formulating reference criteria for the treatment factors of the vitamin D deficiency and prognostic factors of the COVID-19 using 25(OH)D reference value in different regions.


Subject(s)
COVID-19 , Vitamin D Deficiency , Aged , China/epidemiology , Geography , Humans , Spatial Analysis , Vitamin D/analogs & derivatives , Vitamin D Deficiency/epidemiology
11.
Stud Health Technol Inform ; 290: 1046-1047, 2022 Jun 06.
Article in English | MEDLINE | ID: covidwho-1933592

ABSTRACT

PREDIMED, Clinical Data Warehouse of Grenoble Alps University Hospital, is currently participating in daily COVID-19 epidemic follow-up via spatial and chronological analysis of geographical maps. This monitoring is aimed for cluster detection and vulnerable population discovery. Our real-time geographical representations allow us to track the epidemic both inside and outside the hospital.


Subject(s)
COVID-19 , COVID-19/epidemiology , Data Warehousing , Geography , Hospitals, University , Humans
12.
PLoS One ; 17(2): e0262305, 2022.
Article in English | MEDLINE | ID: covidwho-1910487

ABSTRACT

BACKGROUND: Widespread vaccination coverage is essential for reducing the COVID-19 havoc and regarded as a crucial tool in restoring normal life on university campuses. Therefore, our research aimed to understand the intention to be vaccinated for COVID-19 among Pakistani university students. METHODS: This cross-sectional study was conducted in five administrative units of Pakistan, i.e., Punjab, Sindh, Balochistan, Azad Jammu and Kashmir, and Khyber Pakhtunkhwa. We obtained data from 2,865 university students between 17th January and 2nd February, 2021, using a semi-structured and self-administered questionnaire. We used Stata (version 16.1, StataCorp LLC) for data management and analysis. RESULTS: The majority (72.5%) of our respondents were willing to take COVID-19 vaccine. The current level of education had a statistically significant relationship with the intention to be vaccinated (p < 0.05). Respondents answered 11 questions encompassing five different domains of the Health Belief Model (HBM). All the items of HBM were significantly associated with the positive intention towards receiving the vaccine (p < 0.05). We conducted a multivariable logistic regression analysis to assess the relative contribution of different factors towards the intention to receive COVID-19 vaccine. Multiple factors such as belief that vaccination should be mandatory for everyone (AOR: 3.99, 95% CI: 3.20-4.98) and willingness to take vaccine even if it is not free (AOR: 3.91, 95% CI: 3.18-4.81) were observed to be associated with high odds of showing willingness to be vaccinated against COVID-19. CONCLUSION: Most of our study participants intended to take vaccines based on their belief regarding the high effectiveness of COVID-19 vaccine. But as rumor-mongers are generating and spreading conspiracy theories daily, the health department and policymakers need to undertake evidence-based campaigns through electronic and social media to ensure expected countrywide vaccination coverage. In this case, our study findings can serve as a foundation for them to ensure mass vaccination coverage among university students, which is crucial now to reopen the dormitories and restore everyday life on campuses.


Subject(s)
COVID-19 Vaccines/immunology , Students , Universities , Female , Geography , Health Knowledge, Attitudes, Practice , Humans , Logistic Models , Male , Multivariate Analysis , Pakistan , ROC Curve , Vaccination
13.
Sante Publique ; Vol. 33(6): 847-852, 2022 Mar 11.
Article in French | MEDLINE | ID: covidwho-1911800

ABSTRACT

INTRODUCTION: In the midst of the COVID-19 health crisis, the Regional Health Observatories (RHO) and the National Federation of RHOs have chosen to make available their expertise regarding development and production of health indicators to support local and national public policies available, in order to plan for the lifting of population lockdown measures. PURPOSE OF RESEARCH: To characterize as finely as possible the geographical territories, including overseas territories, using indicators to describe both the population potentially at risk of presenting serious forms of COVID-19 and the demographic and social situations that could favor the circulation of the Sars-Cov-2 virus. RESULTS: 1,250 profile sheets, one for each public establishment of intermunicipal cooperation in the French departments (excluding Mayotte) presenting 34 indicators were produced. A national synthesis including a typology of these territories in seven classes was also produced. CONCLUSION: This work shows the possibility of describing a series of indicators linked to a specific theme systematically and at fine geographical scales. Along with a typology of territories, this tool can contribute with others to the management of a health crisis.


Subject(s)
COVID-19 , COVID-19/epidemiology , Communicable Disease Control , Geography , Humans , SARS-CoV-2
14.
PLoS Pathog ; 18(5): e1010490, 2022 05.
Article in English | MEDLINE | ID: covidwho-1902645

ABSTRACT

Tuberculosis (TB), one of the deadliest threats to human health, is mainly caused by 2 highly related and human-adapted bacteria broadly known as Mycobacterium tuberculosis and Mycobacterium africanum. Whereas M. tuberculosis is widely spread, M. africanum is restricted to West Africa, where it remains a significant cause of tuberculosis. Although several differences have been identified between these 2 pathogens, M. africanum remains a lot less studied than M. tuberculosis. Here, we discuss the genetic, phenotypic, and clinical similarities and differences between strains of M. tuberculosis and M. africanum. We also discuss our current knowledge on the immune response to M. africanum and how it possibly articulates with distinct disease progression and with the geographical restriction attributed to this pathogen. Understanding the functional impact of the diversity existing in TB-causing bacteria, as well as incorporating this diversity in TB research, will contribute to the development of better, more specific approaches to tackle TB.


Subject(s)
Mycobacterium tuberculosis , Tuberculosis , Africa, Western , Geography , Humans , Mycobacterium tuberculosis/genetics , Tuberculosis/microbiology
15.
Sci Rep ; 12(1): 699, 2022 01 13.
Article in English | MEDLINE | ID: covidwho-1900543

ABSTRACT

The global spread of the COVID-19 pandemic has followed complex pathways, largely attributed to the high virus infectivity, human travel patterns, and the implementation of multiple mitigation measures. The resulting geographic patterns describe the evolution of the epidemic and can indicate areas that are at risk of an outbreak. Here, we analyze the spatial correlations of new active cases in the USA at the county level and characterize the extent of these correlations at different times. We show that the epidemic did not progress uniformly and we identify various stages which are distinguished by significant differences in the correlation length. Our results indicate that the correlation length may be large even during periods when the number of cases declines. We find that correlations between urban centers were much more significant than between rural areas and this finding indicates that long-range spreading was mainly facilitated by travel between cities, especially at the first months of the epidemic. We also show the existence of a percolation transition in November 2020, when the largest part of the country was connected to a spanning cluster, and a smaller-scale transition in January 2021, with both times corresponding to the peak of the epidemic in the country.


Subject(s)
COVID-19/transmission , Cities/statistics & numerical data , Disease Outbreaks/statistics & numerical data , Geography/statistics & numerical data , Humans , Pandemics/statistics & numerical data , SARS-CoV-2/pathogenicity , Travel/statistics & numerical data , United States
16.
Lancet ; 399(10334): 1469-1488, 2022 04 16.
Article in English | MEDLINE | ID: covidwho-1867908

ABSTRACT

BACKGROUND: The infection-fatality ratio (IFR) is a metric that quantifies the likelihood of an individual dying once infected with a pathogen. Understanding the determinants of IFR variation for COVID-19, the disease caused by the SARS-CoV-2 virus, has direct implications for mitigation efforts with respect to clinical practice, non-pharmaceutical interventions, and the prioritisation of risk groups for targeted vaccine delivery. The IFR is also a crucial parameter in COVID-19 dynamic transmission models, providing a way to convert a population's mortality rate into an estimate of infections. METHODS: We estimated age-specific and all-age IFR by matching seroprevalence surveys to total COVID-19 mortality rates in a population. The term total COVID-19 mortality refers to an estimate of the total number of deaths directly attributable to COVID-19. After applying exclusion criteria to 5131 seroprevalence surveys, the IFR analyses were informed by 2073 all-age surveys and 718 age-specific surveys (3012 age-specific observations). When seroprevalence was reported by age group, we split total COVID-19 mortality into corresponding age groups using a Bayesian hierarchical model to characterise the non-linear age pattern of reported deaths for a given location. To remove the impact of vaccines on the estimated IFR age pattern, we excluded age-specific observations of seroprevalence and deaths that occurred after vaccines were introduced in a location. We estimated age-specific IFR with a non-linear meta-regression and used the resulting age pattern to standardise all-age IFR observations to the global age distribution. All IFR observations were adjusted for baseline and waning antibody-test sensitivity. We then modelled age-standardised IFR as a function of time, geography, and an ensemble of 100 of the top-performing covariate sets. The covariates included seven clinical predictors (eg, age-standardised obesity prevalence) and two measures of health system performance. Final estimates for 190 countries and territories, as well as subnational locations in 11 countries and territories, were obtained by predicting age-standardised IFR conditional on covariates and reversing the age standardisation. FINDINGS: We report IFR estimates for April 15, 2020, to January 1, 2021, the period before the introduction of vaccines and widespread evolution of variants. We found substantial heterogeneity in the IFR by age, location, and time. Age-specific IFR estimates form a J shape, with the lowest IFR occurring at age 7 years (0·0023%, 95% uncertainty interval [UI] 0·0015-0·0039) and increasing exponentially through ages 30 years (0·0573%, 0·0418-0·0870), 60 years (1·0035%, 0·7002-1·5727), and 90 years (20·3292%, 14·6888-28·9754). The countries with the highest IFR on July 15, 2020, were Portugal (2·085%, 0·946-4·395), Monaco (1·778%, 1·265-2·915), Japan (1·750%, 1·302-2·690), Spain (1·710%, 0·991-2·718), and Greece (1·637%, 1·155-2·678). All-age IFR varied by a factor of more than 30 among 190 countries and territories. After age standardisation, the countries with the highest IFR on July 15, 2020, were Peru (0·911%, 0·636-1·538), Portugal (0·850%, 0·386-1·793), Oman (0·762%, 0·381-1·399), Spain (0·751%, 0·435-1·193), and Mexico (0·717%, 0·426-1·404). Subnational locations with high IFRs also included hotspots in the UK and southern and eastern states of the USA. Sub-Saharan African countries and Asian countries generally had the lowest all-age and age-standardised IFRs. Population age structure accounted for 74% of logit-scale variation in IFRs estimated for 39 in-sample countries on July 15, 2020. A post-hoc analysis showed that high rates of transmission in the care home population might account for higher IFRs in some locations. Among all countries and territories, we found that the median IFR decreased from 0·466% (interquartile range 0·223-0·840) to 0·314% (0·143-0·551) between April 15, 2020, and Jan 1, 2021. INTERPRETATION: Estimating the IFR for global populations helps to identify relative vulnerabilities to COVID-19. Information about how IFR varies by age, time, and location informs clinical practice and non-pharmaceutical interventions like physical distancing measures, and underpins vaccine risk stratification. IFR and mortality risk form a J shape with respect to age, which previous research, such as that by Glynn and Moss in 2020, has identified to be a common pattern among infectious diseases. Understanding the experience of a population with COVID-19 mortality requires consideration for local factors; IFRs varied by a factor of more than 30 among 190 countries and territories in this analysis. In particular, the presence of elevated age-standardised IFRs in countries with well resourced health-care systems indicates that factors beyond health-care capacity are important. Potential extenuating circumstances include outbreaks among care home residents, variable burdens of severe cases, and the population prevalence of comorbid conditions that increase the severity of COVID-19 disease. During the pre-vaccine period, the estimated 33% decrease in median IFR over 8 months suggests that treatment for COVID-19 has improved over time. Estimating IFR for the pre-vaccine era provides an important baseline for describing the progression of COVID-19 mortality patterns. FUNDING: Bill & Melinda Gates Foundation, J Stanton, T Gillespie, and J and E Nordstrom.


Subject(s)
COVID-19 , Vaccines , Adult , Bayes Theorem , COVID-19/epidemiology , COVID-19/prevention & control , Child , Geography , Global Burden of Disease , Global Health , Humans , SARS-CoV-2 , Seroepidemiologic Studies
17.
BMC Res Notes ; 14(1): 468, 2021 Dec 24.
Article in English | MEDLINE | ID: covidwho-1854866

ABSTRACT

OBJECTIVE: The proliferation of false information on COVID-19 mostly through social media is adversely affecting control efforts. The objective of this study was to identify areas where targeted effective messaging can be useful in demystifying misinformation against COVID-19. RESULTS: The study showed high levels of misinformation on COVID-19 in the study area [mean score 2.71; standard deviation (SD) 1.5]. The highest levels of misinformation were observed in Dr. Ruth Segomotsi Mompati district, North West province (mean score: 3.84; SD: 2.1) and Sedibeng district, Gauteng province (mean score: 3.56; SD 1.7). Higher levels of misinformation were reported by those aged 18-24 years (mean score: 3.48; SD: 1.8), and men (mean score: 2.73; SD: 1.8). Across the two provinces, we identified geospatial hot and coldspots of misinformation highlighting the need to implement point of care strategies such as targeted messaging. Findings showed the need for targeted interventions to young people, students, those with low levels of education and the self-employed in the two districts more importantly, as South Africa expands its nationwide vaccination roll-out.


Subject(s)
COVID-19 , Adolescent , Communication , Geography , Humans , Male , SARS-CoV-2 , South Africa
19.
Infect Dis Poverty ; 11(1): 44, 2022 Apr 15.
Article in English | MEDLINE | ID: covidwho-1793809

ABSTRACT

BACKGROUND: A remarkable drop in tuberculosis (TB) incidence has been achieved in China, although in 2019 it was still considered the second most communicable disease. However, TB's spatial features and risk factors in urban areas remain poorly understood. This study aims to identify the spatial differentiations and potential influencing factors of TB in highly urbanized regions on a fine scale. METHODS: This study included 18 socioeconomic and environmental variables in the four central districts of Guangzhou, China. TB case data obtained from the Guangzhou Institute of Tuberculosis Control and Prevention. Before using Pearson correlation and a geographical detector (GD) to identify potential influencing factors, we conducted a global spatial autocorrelation analysis to select an appropriate spatial scales. RESULTS: Owing to its strong spatial autocorrelation (Moran's I = 0.33, Z = 4.71), the 2 km × 2 km grid was selected as the spatial scale. At this level, TB incidence was closely associated with most socioeconomic variables (0.31 < r < 0.76, P < 0.01). Of five environmental factors, only the concentration of fine particulate matter displayed significant correlation (r = 0.21, P < 0.05). Similarly, in terms of q values derived from the GD, socioeconomic variables had stronger explanatory abilities (0.08 < q < 0.57) for the spatial differentiation of the 2017 incidence of TB than environmental variables (0.06 < q < 0.27). Moreover, a much larger proportion (0.16 < q < 0.89) of the spatial differentiation was interpreted by pairwise interactions, especially those (0.60 < q < 0.89) related to the 2016 incidence of TB, officially appointed medical institutions, bus stops, and road density. CONCLUSIONS: The spatial heterogeneity of the 2017 incidence of TB in the study area was considerably influenced by several socioeconomic and environmental factors and their pairwise interactions on a fine scale. We suggest that more attention should be paid to the units with pairwise interacting factors in Guangzhou. Our study provides helpful clues for local authorities implementing more effective intervention measures to reduce TB incidence in China's municipal areas, which are featured by both a high degree of urbanization and a high incidence of TB.


Subject(s)
Epidemics , Tuberculosis , China/epidemiology , Geography , Humans , Incidence , Spatial Analysis , Tuberculosis/epidemiology
20.
PLoS One ; 17(3): e0264511, 2022.
Article in English | MEDLINE | ID: covidwho-1793514

ABSTRACT

The outbreak of the COVID-19 pandemic has had a large impact on various aspects of life, but questions about its effects on close relationships remain largely unanswered. In the present study, we examined perceived changes in relationship satisfaction at the beginning of the COVID-19 pandemic by using an international sample of 3,243 individuals from 67 different countries, mostly from Italy, the United States, the United Kingdom, Germany, Austria, and Switzerland. In April and May 2020, participants responded to an online survey that included questions about relationship satisfaction, their satisfaction before the pandemic, other relationship aspects (e.g., shared time), special circumstances (e.g., mobility restrictions), and enduring dispositions (e.g., insecure attachment). A decline in time shared with one's partner was most strongly associated with perceived decreases in relationship satisfaction, resulting in a different pattern of findings for cohabiting and non-cohabiting individuals. Among the most influential moderators were anxious and avoidant attachment. The findings offer insights into both aggravating and protecting factors in couples' responses to pandemic-related stressors.


Subject(s)
COVID-19/epidemiology , Interpersonal Relations , Personal Satisfaction , Adolescent , Adult , Aged , Anxiety/epidemiology , Anxiety/psychology , COVID-19/psychology , Cross-Sectional Studies , Family Characteristics , Female , Geography , Humans , Male , Middle Aged , Pandemics , Personality/physiology , SARS-CoV-2/physiology , Sexual Partners , Socioeconomic Factors , Stress, Psychological/epidemiology , Stress, Psychological/psychology , Surveys and Questionnaires , Young Adult
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