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2.
Sci Rep ; 12(1): 2454, 2022 02 14.
Article in English | MEDLINE | ID: covidwho-1684113

ABSTRACT

COVID-19 has affected all countries. Its containment represents a unique challenge for India due to a large population (> 1.38 billion) across a wide range of population densities. Assessment of the COVID-19 disease burden is required to put the disease impact into context and support future pandemic policy development. Here, we present the national-level burden of COVID-19 in India in 2020 that accounts for differences across urban and rural regions and across age groups. Input data were collected from official records or published literature. The proportion of excess COVID-19 deaths was estimated using the Institute for Health Metrics and Evaluation, Washington data. Disability-adjusted life years (DALY) due to COVID-19 were estimated in the Indian population in 2020, comprised of years of life lost (YLL) and years lived with disability (YLD). YLL was estimated by multiplying the number of deaths due to COVID-19 by the residual standard life expectancy at the age of death due to the disease. YLD was calculated as a product of the number of incident cases of COVID-19, disease duration and disability weight. Scenario analyses were conducted to account for excess deaths not recorded in the official data and for reported COVID-19 deaths. The direct impact of COVID-19 in 2020 in India was responsible for 14,100,422 (95% uncertainty interval [UI] 14,030,129-14,213,231) DALYs, consisting of 99.2% (95% UI 98.47-99.64%) YLLs and 0.80% (95% UI 0.36-1.53) YLDs. DALYs were higher in urban (56%; 95% UI 56-57%) than rural areas (44%; 95% UI 43.4-43.6) and in men (64%) than women (36%). In absolute terms, the highest DALYs occurred in the 51-60-year-old age group (28%) but the highest DALYs per 100,000 persons were estimated for the 71-80 years old age group (5481; 95% UI 5464-5500 years). There were 4,815,908 (95% UI 4,760,908-4,924,307) DALYs after considering reported COVID-19 deaths only. The DALY estimations have direct and immediate implications not only for public policy in India, but also internationally given that India represents one sixth of the world's population.


Subject(s)
COVID-19/prevention & control , Disability-Adjusted Life Years , Public Health/statistics & numerical data , Quality-Adjusted Life Years , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/epidemiology , COVID-19/virology , Child , Female , Humans , India/epidemiology , Male , Middle Aged , Pandemics/prevention & control , Public Health/methods , Rural Population/statistics & numerical data , SARS-CoV-2/physiology , Urban Population/statistics & numerical data , Young Adult
3.
Antimicrob Resist Infect Control ; 11(1): 34, 2022 02 14.
Article in English | MEDLINE | ID: covidwho-1679967

ABSTRACT

BACKGROUND: The current Coronavirus disease pandemic reveals political and structural inequities of the world's poorest people who have little or no access to health care and yet the largest burdens of poor health. This is in parallel to a more persistent but silent global health crisis, antimicrobial resistance (AMR). We explore the fundamental challenges of health care in humans and animals in relation to AMR in Tanzania. METHODS: We conducted 57 individual interviews and focus groups with providers and patients in high, middle and lower tier health care facilities and communities across three regions of Tanzania between April 2019 and February 2020. We covered topics from health infrastructure and prescribing practices to health communication and patient experiences. RESULTS: Three interconnected themes emerged about systemic issues impacting health. First, there are challenges around infrastructure and availability of vital resources such as healthcare staff and supplies. Second, health outcomes are predicated on patient and provider access to services as well as social determinants of health. Third, health communication is critical in defining trusted sources of information, and narratives of blame emerge around health outcomes with the onus of responsibility for action falling on individuals. CONCLUSION: Entanglements between infrastructure, access and communication exist while constraints in the health system lead to poor health outcomes even in 'normal' circumstances. These are likely to be relevant across the globe and highly topical for addressing pressing global health challenges. Redressing structural health inequities can better equip countries and their citizens to not only face pandemics but also day-to-day health challenges.


Subject(s)
Health Services Accessibility/standards , Poverty/statistics & numerical data , Public Health/standards , Social Determinants of Health/standards , Animals , COVID-19/epidemiology , COVID-19/prevention & control , Global Health/standards , Global Health/statistics & numerical data , Health Services Accessibility/economics , Health Services Accessibility/statistics & numerical data , Humans , Public Health/statistics & numerical data , Social Determinants of Health/economics , Social Determinants of Health/statistics & numerical data , Tanzania/epidemiology
4.
Viruses ; 14(2)2022 01 27.
Article in English | MEDLINE | ID: covidwho-1662708

ABSTRACT

We aimed to analyze the situation of the first two epidemic waves in Myanmar using the publicly available daily situation of COVID-19 and whole-genome sequencing data of SARS-CoV-2. From March 23 to December 31, 2020, there were 33,917 confirmed cases and 741 deaths in Myanmar (case fatality rate of 2.18%). The first wave in Myanmar from March to July was linked to overseas travel, and then a second wave started from Rakhine State, a western border state, leading to the second wave spreading countrywide in Myanmar from August to December 2020. The estimated effective reproductive number (Rt) nationwide reached 6-8 at the beginning of each wave and gradually decreased as the epidemic spread to the community. The whole-genome analysis of 10 Myanmar SARS-CoV-2 strains together with 31 previously registered strains showed that the first wave was caused by GISAID clade O or PANGOLIN lineage B.6 and the second wave was changed to clade GH or lineage B.1.36.16 with a close genetic relationship with other South Asian strains. Constant monitoring of epidemiological situations combined with SARS-CoV-2 genome analysis is important for adjusting public health measures to mitigate the community transmissions of COVID-19.


Subject(s)
COVID-19/epidemiology , Community-Acquired Infections/epidemiology , Community-Acquired Infections/virology , Epidemics/statistics & numerical data , Public Health/statistics & numerical data , SARS-CoV-2/genetics , Adult , Aged , COVID-19/transmission , Child , Community-Acquired Infections/transmission , Female , Genome, Viral , Humans , Male , Middle Aged , Mutation , Myanmar/epidemiology , Phylogeny , SARS-CoV-2/classification , Whole Genome Sequencing , Young Adult
5.
PLoS One ; 17(1): e0261759, 2022.
Article in English | MEDLINE | ID: covidwho-1643248

ABSTRACT

In the beginning of the COVID-19 US epidemic in March 2020, sweeping lockdowns and other aggressive measures were put in place and retained in many states until end of August of 2020; the ensuing economic downturn has led many to question the wisdom of the early COVID-19 policy measures in the US. This study's objective was to evaluate the cost and benefit of the US COVID-19-mitigating policy intervention during the first six month of the pandemic in terms of COVID-19 mortality potentially averted, versus mortality potentially attributable to the economic downturn. We conducted a synthesis-based retrospective cost-benefit analysis of the full complex of US federal, state, and local COVID-19-mitigating measures, including lockdowns and all other COVID-19-mitigating measures, against the counterfactual scenario involving no public health intervention. We derived parameter estimates from a rapid review and synthesis of recent epidemiologic studies and economic literature on regulation-attributable mortality. According to our estimates, the policy intervention saved 866,350-1,711,150 lives (4,886,214-9,650,886 quality-adjusted life-years), while mortality attributable to the economic downturn was 57,922-245,055 lives (2,093,811-8,858,444 life-years). We conclude that the number of lives saved by the spring-summer lockdowns and other COVID-19-mitigation was greater than the number of lives potentially lost due to the economic downturn. However, the net impact on quality-adjusted life expectancy is ambiguous.


Subject(s)
COVID-19/epidemiology , Cost-Benefit Analysis/statistics & numerical data , Models, Statistical , Public Health/economics , Quality-Adjusted Life Years , Quarantine/economics , COVID-19/economics , Communicable Disease Control/economics , Communicable Disease Control/methods , Humans , Public Health/statistics & numerical data , Quality of Life/psychology , Quarantine/ethics , Retrospective Studies , SARS-CoV-2/pathogenicity , United States/epidemiology
6.
Nat Commun ; 13(1): 411, 2022 01 20.
Article in English | MEDLINE | ID: covidwho-1641963

ABSTRACT

Prior research using electronic health records for Covid-19 vaccine safety monitoring typically focuses on specific disease groups and excludes individuals with multimorbidity, defined as ≥2 chronic conditions. We examine the potential additional risk of adverse events 28 days after the first dose of CoronaVac or Comirnaty imposed by multimorbidity. Using a territory-wide public healthcare database with population-based vaccination records in Hong Kong, we analyze a retrospective cohort of patients with chronic conditions. Thirty adverse events of special interest according to the World Health Organization are examined. In total, 883,416 patients are included and 2,807 (0.3%) develop adverse events. Results suggest vaccinated patients have lower risks of adverse events than unvaccinated individuals, multimorbidity is associated with increased risks regardless of vaccination, and the association of vaccination with adverse events is not modified by multimorbidity. To conclude, we find no evidence that multimorbidity imposes extra risks of adverse events following Covid-19 vaccination.


Subject(s)
COVID-19 Vaccines/immunology , COVID-19/immunology , SARS-CoV-2/immunology , Vaccination/statistics & numerical data , Aged , COVID-19/epidemiology , COVID-19/virology , COVID-19 Vaccines/administration & dosage , COVID-19 Vaccines/adverse effects , Databases, Factual/statistics & numerical data , Epidemics/prevention & control , Female , Hong Kong/epidemiology , Humans , Male , Middle Aged , Multimorbidity , Public Health/statistics & numerical data , Retrospective Studies , Risk Factors , SARS-CoV-2/physiology , Vaccination/adverse effects
7.
Sci Rep ; 12(1): 328, 2022 01 10.
Article in English | MEDLINE | ID: covidwho-1616999

ABSTRACT

Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Without existing protective immunity, an EID may spread rapidly and cause mass casualties in a very short time. Therefore, it is imperative to identify cases with risk of disease progression for the optimized allocation of medical resources in case medical facilities are overwhelmed with a flood of patients. This study has aimed to cope with this challenge from the aspect of preventive medicine by exploiting machine learning technologies. The study has been based on 83,227 hospital admissions with influenza-like illness and we analysed the risk effects of 19 comorbidities along with age and gender for severe illness or mortality risk. The experimental results revealed that the decision rules derived from the machine learning based prediction models can provide valuable guidelines for the healthcare policy makers to develop an effective vaccination strategy. Furthermore, in case the healthcare facilities are overwhelmed by patients with EID, which frequently occurred in the recent COVID-19 pandemic, the frontline physicians can incorporate the proposed prediction models to triage patients suffering minor symptoms without laboratory tests, which may become scarce during an EID disaster. In conclusion, our study has demonstrated an effective approach to exploit machine learning technologies to cope with the challenges faced during the outbreak of an EID.


Subject(s)
COVID-19/epidemiology , Communicable Diseases, Emerging/epidemiology , Hospitalization/statistics & numerical data , Machine Learning , Preventive Medicine/statistics & numerical data , Public Health/statistics & numerical data , COVID-19/prevention & control , COVID-19/virology , Communicable Diseases, Emerging/prevention & control , Hospital Mortality , Humans , International Classification of Diseases , Logistic Models , Models, Theoretical , Pandemics/prevention & control , Preventive Medicine/methods , Public Health/methods , Risk Factors , SARS-CoV-2/physiology , Severity of Illness Index
8.
Malar J ; 21(1): 10, 2022 Jan 04.
Article in English | MEDLINE | ID: covidwho-1590595

ABSTRACT

BACKGROUND: The use of data in targeting malaria control efforts is essential for optimal use of resources. This work provides a practical mechanism for prioritizing geographic areas for insecticide-treated net (ITN) distribution campaigns in settings with limited resources. METHODS: A GIS-based weighted approach was adopted to categorize and rank administrative units based on data that can be applied in various country contexts where Plasmodium falciparum transmission is reported. Malaria intervention and risk factors were used to rank local government areas (LGAs) in Nigeria for prioritization during mass ITN distribution campaigns. Each factor was assigned a unique weight that was obtained through application of the analytic hierarchy process (AHP). The weight was then multiplied by a value based on natural groupings inherent in the data, or the presence or absence of a given intervention. Risk scores for each factor were then summated to generate a composite unique risk score for each LGA. This risk score was translated into a prioritization map which ranks each LGA from low to high priority in terms of timing of ITN distributions. RESULTS: A case study using data from Nigeria showed that a major component that influenced the prioritization scheme was ITN access. Sensitivity analysis results indicate that changes to the methodology used to quantify ITN access did not modify outputs substantially. Some 120 LGAs were categorized as 'extremely high' or 'high' priority when a spatially interpolated ITN access layer was used. When prioritization scores were calculated using DHS-reported state level ITN access, 108 (90.0%) of the 120 LGAs were also categorized as being extremely high or high priority. The geospatial heterogeneity found among input risk factors suggests that a range of variables and covariates should be considered when using data to inform ITN distributions. CONCLUSION: The authors provide a tool for prioritizing regions in terms of timing of ITN distributions. It serves as a base upon which a wider range of vector control interventions could be targeted. Its value added can be found in its potential for application in multiple country contexts, expediated timeframe for producing outputs, and its use of systematically collected malaria indicators in informing prioritization.


Subject(s)
Insecticide-Treated Bednets/statistics & numerical data , Mosquito Control/methods , Public Health/statistics & numerical data , Spatial Analysis , Child, Preschool , Emergencies , Humans , Infant , Nigeria
9.
J Med Internet Res ; 23(2): e25734, 2021 02 12.
Article in English | MEDLINE | ID: covidwho-1575972

ABSTRACT

BACKGROUND: In a fast-evolving public health crisis such as the COVID-19 pandemic, multiple pieces of relevant information can be posted sequentially on a social media platform. The interval between subsequent posting times may have a different impact on the transmission and cross-propagation of the old and new information that results in a different peak value and a final size of forwarding users of the new information, depending on the content correlation and whether the new information is posted during the outbreak or quasi-steady-state phase of the old information. OBJECTIVE: This study aims to help in designing effective communication strategies to ensure information is delivered to the maximal number of users. METHODS: We developed and analyzed two classes of susceptible-forwarding-immune information propagation models with delay in transmission to describe the cross-propagation process of relevant information. A total of 28,661 retweets of typical information were posted frequently by each opinion leader related to COVID-19 with high influence (data acquisition up to February 19, 2020). The information was processed into discrete points with a frequency of 10 minutes, and the real data were fitted by the model numerical simulation. Furthermore, the influence of parameters on information dissemination and the design of a publishing strategy were analyzed. RESULTS: The current epidemic outbreak situation, epidemic prevention, and other related authoritative information cannot be timely and effectively browsed by the public. The ingenious use of information release intervals can effectively enhance the interaction between information and realize the effective diffusion of information. We parameterized our models using real data from Sina Microblog and used the parameterized models to define and evaluate mutual attractiveness indexes, and we used these indexes and parameter sensitivity analyses to inform optimal strategies for new information to be effectively propagated in the microblog. The results of the parameter analysis showed that using different attractiveness indexes as the key parameters can control the information transmission with different release intervals, so it is considered as a key link in the design of an information communication strategy. At the same time, the dynamic process of information was analyzed through index evaluation. CONCLUSIONS: Our model can carry out an accurate numerical simulation of information at different release intervals and achieve a dynamic evaluation of information transmission by constructing an indicator system so as to provide theoretical support and strategic suggestions for government decision making. This study optimizes information posting strategies to maximize communication efforts for delivering key public health messages to the public for better outcomes of public health emergency management.


Subject(s)
COVID-19/epidemiology , Health Education , Information Dissemination , Public Health/statistics & numerical data , Public Opinion , Social Media/statistics & numerical data , Communication , Disease Outbreaks , Government , Humans , Pandemics , Time Factors
10.
PLoS One ; 16(11): e0259590, 2021.
Article in English | MEDLINE | ID: covidwho-1542180

ABSTRACT

BACKGROUND: Public health services and systems research is under-developed in Canada and this is particularly the case with respect to research on local public health unit operational functioning and capacity. The purpose of this paper is to report on a study that will collect retrospective information on the local public health response to COVID-19 throughout Canada between 2020 and 2021. METHODS/DESIGN: The goal of the study is to develop and implement a study framework that will collect retrospective information on the local public health system response to the COVID-19 pandemic in Canada. This study will involve administering a mixed-method survey to Medical Health Officers/Medical Officers of Health in every local and regional public health unit across the country, followed by a process of coding and grouping these responses in a consistent and comparable way. Coded responses will be assessed for patterns of divergent or convergent roles and approaches of local public health across the country with respect to interventions in their response to COVID-19. The Framework Method of thematic analysis will be applied to assess the qualitative answers to the open-ended questions that speak to public health policy features. DISCUSSION: The strengths of the study protocol include the engagement of Medical Health Officers/Medical Officers of Health as research partners and a robust integrated knowledge translation approach to further public health services and systems research in Canada.


Subject(s)
COVID-19/epidemiology , Pandemics/prevention & control , Public Health/statistics & numerical data , Canada/epidemiology , Clinical Protocols , Humans , Retrospective Studies , Surveys and Questionnaires
11.
J Biomed Semantics ; 12(1): 13, 2021 07 18.
Article in English | MEDLINE | ID: covidwho-1484319

ABSTRACT

BACKGROUND: Effective response to public health emergencies, such as we are now experiencing with COVID-19, requires data sharing across multiple disciplines and data systems. Ontologies offer a powerful data sharing tool, and this holds especially for those ontologies built on the design principles of the Open Biomedical Ontologies Foundry. These principles are exemplified by the Infectious Disease Ontology (IDO), a suite of interoperable ontology modules aiming to provide coverage of all aspects of the infectious disease domain. At its center is IDO Core, a disease- and pathogen-neutral ontology covering just those types of entities and relations that are relevant to infectious diseases generally. IDO Core is extended by disease and pathogen-specific ontology modules. RESULTS: To assist the integration and analysis of COVID-19 data, and viral infectious disease data more generally, we have recently developed three new IDO extensions: IDO Virus (VIDO); the Coronavirus Infectious Disease Ontology (CIDO); and an extension of CIDO focusing on COVID-19 (IDO-COVID-19). Reflecting the fact that viruses lack cellular parts, we have introduced into IDO Core the term acellular structure to cover viruses and other acellular entities studied by virologists. We now distinguish between infectious agents - organisms with an infectious disposition - and infectious structures - acellular structures with an infectious disposition. This in turn has led to various updates and refinements of IDO Core's content. We believe that our work on VIDO, CIDO, and IDO-COVID-19 can serve as a model for yielding greater conformance with ontology building best practices. CONCLUSIONS: IDO provides a simple recipe for building new pathogen-specific ontologies in a way that allows data about novel diseases to be easily compared, along multiple dimensions, with data represented by existing disease ontologies. The IDO strategy, moreover, supports ontology coordination, providing a powerful method of data integration and sharing that allows physicians, researchers, and public health organizations to respond rapidly and efficiently to current and future public health crises.


Subject(s)
Biological Ontologies/statistics & numerical data , COVID-19/prevention & control , Communicable Disease Control/statistics & numerical data , Communicable Diseases/therapy , Computational Biology/statistics & numerical data , SARS-CoV-2/isolation & purification , COVID-19/epidemiology , COVID-19/virology , Communicable Disease Control/methods , Communicable Diseases/epidemiology , Communicable Diseases/transmission , Computational Biology/methods , Data Mining/methods , Data Mining/statistics & numerical data , Epidemics , Humans , Information Dissemination/methods , Public Health/methods , Public Health/statistics & numerical data , SARS-CoV-2/physiology , Semantics
12.
Biomed Res Int ; 2021: 7787624, 2021.
Article in English | MEDLINE | ID: covidwho-1476885

ABSTRACT

The ascendancy of coronavirus has become widespread all around the world. For the prevention of viral transmission, the pattern of disease is explored. Epidemiological modeling is a vital component of the research. These models assist in studying various aspects of infectious diseases, such as death, recovery, and infection rates. Coronavirus trends across several countries may analyze sufficiently using SIR, SEIR, and SIQR models. Across this study, we propose two modified versions of the SEIRD method for evaluating the transmission of this infectious disease in the South Asian countries, more precisely, in the south Asian subcontinent. The SEIRD model is updated further by fusing some new factors, namely, isolation for the suspected people and recovery and death of the people who are not under the coverage of healthcare schemes or reluctant to receive treatment for various catastrophes. We will investigate the influences of those ingredients on public health-related issues. Finally, we will predict and display the infection scenario and relevant elements with the concluding remarks through the statistical analysis.


Subject(s)
COVID-19/epidemiology , Models, Theoretical , Asia/epidemiology , Bangladesh/epidemiology , Developing Countries , Humans , Infection Control/statistics & numerical data , Physical Distancing , Public Health/statistics & numerical data
13.
Parasit Vectors ; 14(1): 517, 2021 Oct 07.
Article in English | MEDLINE | ID: covidwho-1463263

ABSTRACT

BACKGROUND: Although visceral leishmaniasis (VL) was largely brought under control in most regions of China during the previous century, VL cases have rebounded in western and central China in recent decades. The aim of this study was to investigate the epidemiological features and spatial-temporal distribution of VL in mainland China from 2004 to 2019. METHODS: Incidence and mortality data for VL during the period 2004-2019 were collected from the Public Health Sciences Data Center of China and annual national epidemic reports of VL, whose data source was the National Diseases Reporting Information System. Joinpoint regression analysis was performed to explore the trends of VL. Spatial autocorrelation and spatial-temporal clustering analysis were conducted to identify the distribution and risk areas of VL transmission. RESULTS: A total of 4877 VL cases were reported in mainland China during 2004-2019, with mean annual incidence of 0.0228/100,000. VL incidence showed a decreasing trend in general during our study period (annual percentage change [APC] = -4.2564, 95% confidence interval [CI]: -8.0856 to -0.2677). Among mainly endemic provinces, VL was initially heavily epidemic in Gansu, Sichuan, and especially Xinjiang, but subsequently decreased considerably. In contrast, Shaanxi and Shanxi witnessed significantly increasing trends, especially in 2017-2019. The first-level spatial-temporal aggregation area covered two endemic provinces in northwestern China, including Gansu and Xinjiang, with the gathering time from 2004 to 2011 (relative risk [RR] = 13.91, log-likelihood ratio [LLR] = 3308.87, P < 0.001). The secondary aggregation area was detected in Shanxi province of central China, with the gathering time of 2019 (RR = 1.61, LLR = 4.88, P = 0.041). The epidemic peak of October to November disappeared in 2018-2019, leaving only one peak in March to May. CONCLUSIONS: Our findings suggest that VL is still an important endemic infectious disease in China. Epidemic trends in different provinces changed significantly and spatial-temporal aggregation areas shifted from northwestern to central China during our study period. Mitigation strategies, including large-scale screening, insecticide spraying, and health education encouraging behavioral change, in combination with other integrated approaches, are needed to decrease transmission risk in areas at risk, especially in Shanxi, Shaanxi, and Gansu provinces.


Subject(s)
Epidemics/statistics & numerical data , Epidemiological Monitoring , Leishmaniasis, Visceral/epidemiology , Public Health/statistics & numerical data , Spatio-Temporal Analysis , Adolescent , Child , Child, Preschool , China/epidemiology , Humans , Incidence , Infant , Infant, Newborn , Leishmaniasis, Visceral/mortality , Population
14.
PLoS One ; 16(6): e0252803, 2021.
Article in English | MEDLINE | ID: covidwho-1453123

ABSTRACT

A variety of infectious diseases occur in mainland China every year. Cyclic oscillation is a widespread attribute of most viral human infections. Understanding the outbreak cycle of infectious diseases can be conducive for public health management and disease surveillance. In this study, we collected time-series data for 23 class B notifiable infectious diseases from 2004 to 2020 using public datasets from the National Health Commission of China. Oscillatory properties were explored using power spectrum analysis. We found that the 23 class B diseases from the dataset have obvious oscillatory patterns (seasonal or sporadic), which could be divided into three categories according to their oscillatory power in different frequencies each year. These diseases were found to have different preferred outbreak months and infection selectivity. Diseases that break out in autumn and winter are more selective. Furthermore, we calculated the oscillation power and the average number of infected cases of all 23 diseases in the first eight years (2004 to 2012) and the next eight years (2012 to 2020) since the update of the surveillance system. A strong positive correlation was found between the change of oscillation power and the change in the number of infected cases, which was consistent with the simulation results using a conceptual hybrid model. The establishment of reliable and effective analytical methods contributes to a better understanding of infectious diseases' oscillation cycle characteristics. Our research has certain guiding significance for the effective prevention and control of class B infectious diseases.


Subject(s)
Algorithms , Communicable Diseases/epidemiology , Disease Outbreaks , Models, Theoretical , Seasons , China/epidemiology , Communicable Diseases/classification , Communicable Diseases/diagnosis , Humans , Incidence , Infection Control/methods , Infection Control/statistics & numerical data , Population Surveillance/methods , Public Health/methods , Public Health/statistics & numerical data
15.
Glob Health Res Policy ; 6(1): 37, 2021 09 30.
Article in English | MEDLINE | ID: covidwho-1448492

ABSTRACT

BACKGROUND: COVID-19 has seriously affected people's mental health and changed their behaviors. Previous studies for mental state and behavior promotion only targeted limited people or were not suitable for daily activity restrictions. Therefore, we decided to explore the effect of health education videos on people's mental state and health-related behaviors. METHODS: Based on WeChat, QQ, and other social media, we conducted an online survey by snowball sampling. Spearman's non-parametric method was used to analyze the correlation related to mental health problems and health-related behaviors. Besides, we used binary logistic regression analyses to examine mental health problems and health-related behaviors' predictors. We performed SPSS macro PROCESS (model 4 and model 6) to analyze mediation relationships between exposure to health education videos and depression/anxiety/health-related behaviors. These models were regarded as exploratory. RESULTS: Binary logistic regression analyses indicated that people who watched the health education videos were more likely to wear masks (OR 1.15, p < 0.001), disinfect (OR 1.26, p < 0.001), and take temperature (OR 1.37, p < 0.001). With higher level of posttraumatic growth (PTG) or perceived social support (PSS), people had lower percentage of depression (For PSS, OR 0.98, p < 0.001; For PTG, OR 0.98, p < 0.01) and anxiety (For PSS, OR 0.98, p < 0.001; For PTG, OR 0.98, p = 0.01) and better health behaviors. The serial multiple-mediation model supported the positive indirect effects of exposure to health education videos on the depression and three health-related behaviors through PSS and PTG (Depression: B[SE] = - 0.0046 [0.0021], 95% CI - 0.0098, - 0.0012; Mask-wearing: B[SE] = 0.0051 [0.0023], 95% CI 0.0015, 0.0010; Disinfection: B[SE] = 0.0059 [0.0024], 95% CI 0.0024, 0.0012; Temperature-taking: B[SE] = 0.0067 [0.0026], 95% CI 0.0023, 0.0013). CONCLUSION: Exposure to health education videos can improve people's self-perceived social support and inner growth and help them cope with the adverse impact of public health emergencies with better mental health and health-related behaviors.


Subject(s)
COVID-19/psychology , Health Behavior , Health Education/statistics & numerical data , Mental Health/statistics & numerical data , Public Health/statistics & numerical data , Adult , Aged , China , Female , Health Education/methods , Humans , Male , Middle Aged , Social Support , Young Adult
16.
PLoS One ; 16(9): e0257428, 2021.
Article in English | MEDLINE | ID: covidwho-1435612

ABSTRACT

INTRODUCTION: Twitter represents a mainstream news source for the American public, offering a valuable vehicle for learning how citizens make sense of pandemic health threats like Covid-19. Masking as a risk mitigation measure became controversial in the US. The social amplification risk framework offers insight into how a risk event interacts with psychological, social, institutional, and cultural communication processes to shape Covid-19 risk perception. METHODS: Qualitative content analysis was conducted on 7,024 mask tweets reflecting 6,286 users between January 24 and July 7, 2020, to identify how citizens expressed Covid-19 risk perception over time. Descriptive statistics were computed for (a) proportion of tweets using hyperlinks, (b) mentions, (c) hashtags, (d) questions, and (e) location. RESULTS: Six themes emerged regarding how mask tweets amplified and attenuated Covid-19 risk: (a) severity perceptions (18.0%) steadily increased across 5 months; (b) mask effectiveness debates (10.7%) persisted; (c) who is at risk (26.4%) peaked in April and May 2020; (d) mask guidelines (15.6%) peaked April 3, 2020, with federal guidelines; (e) political legitimizing of Covid-19 risk (18.3%) steadily increased; and (f) mask behavior of others (31.6%) composed the largest discussion category and increased over time. Of tweets, 45% contained a hyperlink, 40% contained mentions, 33% contained hashtags, and 16.5% were expressed as a question. CONCLUSIONS: Users ascribed many meanings to mask wearing in the social media information environment revealing that COVID-19 risk was expressed in a more expanded range than objective risk. The simultaneous amplification and attenuation of COVID-19 risk perception on social media complicates public health messaging about mask wearing.


Subject(s)
COVID-19/prevention & control , Masks/virology , Pandemics/prevention & control , Social Media/statistics & numerical data , Communication , Humans , Longitudinal Studies , Perception/physiology , Public Health/statistics & numerical data , Public Opinion , Risk-Taking , SARS-CoV-2/pathogenicity , United States
17.
Global Health ; 17(1): 111, 2021 09 19.
Article in English | MEDLINE | ID: covidwho-1430460

ABSTRACT

Ten years of the Syrian war had a devastating effect on Syrian lives, including millions of refugees and displaced people, enormous destruction in the infrastructure, and the worst economic crisis Syria has ever faced. The health sector was hit hard by this war, up to 50% of the health facilities have been destroyed and up to 70% of the healthcare providers fled the country seeking safety, which increased the workload and mental pressure for the remaining medical staff. Five databases were searched and 438 articles were included according to the inclusion criteria, the articles were divided into categories according to the topic of the article.Through this review, the current health status of the Syrian population living inside Syria, whether under governmental or opposition control, was reviewed, and also, the health status of the Syrian refugees was examined according to each host country. Public health indicators were used to summarize and categorize the information. This research reviewed mental health, children and maternal health, oral health, non-communicable diseases, infectious diseases, occupational health, and the effect of the COVID - 19 pandemic on the Syrian healthcare system. The results of the review are irritating, as still after ten years of war and millions of refugees there is an enormous need for healthcare services, and international organization has failed to respond to those needs. The review ended with the current and future challenges facing the healthcare system, and suggestions about rebuilding the healthcare system.Through this review, the major consequences of the Syrian war on the health of the Syrian population have been reviewed and highlighted. Considerable challenges will face the future of health in Syria which require the collaboration of the health authorities to respond to the growing needs of the Syrian population. This article draws an overview about how the Syrian war affected health sector for Syrian population inside and outside Syria after ten years of war which makes it an important reference for future researchers to get the main highlight of the health sector during the Syrian crisis.


Subject(s)
Public Health/standards , Refugees/statistics & numerical data , Warfare/statistics & numerical data , Altruism , Developing Countries/statistics & numerical data , Health Resources/supply & distribution , Health Resources/trends , Health Services Accessibility/standards , Humans , Public Health/statistics & numerical data , Public Health/trends , Syria
18.
JMIR Public Health Surveill ; 7(9): e31930, 2021 09 17.
Article in English | MEDLINE | ID: covidwho-1417047

ABSTRACT

This report aimed to provide an overview of the epidemiological situation of COVID-19 in Morocco and to review the actions carried out as part of the national response to this pandemic. The methodology adopted was based on literature review, interviews with officials and actors in the field, and remote discussion workshops with a multidisciplinary and multisectoral working group. Morocco took advantage of the capacities already strengthened within the framework of the application of the provisions of the International Health Regulations (IHR) of 2005. A SWOT analysis made it possible to note that an unprecedented political commitment enabled all the necessary means to face the pandemic and carry out all the response activities, including a campaign of relentless communication. Nevertheless, and despite the efforts made, the shortage of human resources, especially those qualified in intensive care and resuscitation, has been the main drawback to be addressed. The main lesson learned is a need to further strengthen national capacities to prepare for and respond to possible public health emergencies and to embark on a process overhaul of the health system, including research into innovative tools to ensure the continuity of the various disease prevention and control activities. In addition, response to a health crisis is not only the responsibility of the health sector but also intersectoral collaboration is needed to guarantee an optimal coordinated fight. Community-oriented approaches in public health have to be strengthened through more participation and involvement of nongovernmental organizations (NGOs) and civil society in operational and strategic planning.


Subject(s)
COVID-19/prevention & control , Public Health/methods , COVID-19/epidemiology , COVID-19 Testing/methods , COVID-19 Testing/standards , Humans , Morocco/epidemiology , Public Health/statistics & numerical data , Quarantine/psychology , Quarantine/standards , Workforce/standards
19.
PLoS One ; 16(9): e0257291, 2021.
Article in English | MEDLINE | ID: covidwho-1416893

ABSTRACT

The outbreak of a novel coronavirus pneumonia (COVID-19), wherein more than 200 million people have been infected and millions have died, poses a great threat to achieving the United Nations 2030 sustainable development goal (SDGs). Based on the Baidu index of 'novel coronavirus', this paper analyses the spatial and temporal characteristics of and factors that influenced the attention network for COVID-19 from January 9, 2020, to April 15, 2020. The study found that (1) Temporally, the attention in the new coronavirus network showed an upward trend from January 9 to January 29, with the largest increase from January 23 to January 29 and a peak on January 29, and then a slow downward trend. The level of attention in the new coronavirus network was basically flat when comparing January 22 and March 4. (2) Spatially, first, from the perspective of regional differences, the network attention in the eastern and central regions decreased in turn. The network users in the eastern region exhibited the highest attention to the new coronavirus, especially in Guangdong, Shandong, Jiangsu and other provinces and cities. The network attention in Tibet, Xinjiang, Qinghai and Ningxia in the western region was the lowest in terms of the national network attention. Second, from the perspective of interprovincial differences, the attention in the new coronavirus network was highly consistent with the Hu Huanyong line of China's population boundary. The east of the Hu Huanyong line is densely populated, and the network showed high concern, mostly ranking at the third to fifth levels. (3) The number of Internet users in the information technology field, the population, and the culture and age characteristics of individuals are important factors that influence the novel coronavirus attention network.


Subject(s)
COVID-19/prevention & control , Information Dissemination/methods , Internet/statistics & numerical data , Online Social Networking , Spatio-Temporal Analysis , Algorithms , COVID-19/epidemiology , COVID-19/virology , China/epidemiology , Epidemics , Geography , Humans , Internet/trends , Models, Theoretical , Public Health/methods , Public Health/statistics & numerical data , Public Health/trends , SARS-CoV-2/physiology , Time Factors
20.
Mayo Clin Proc ; 96(12): 3042-3052, 2021 12.
Article in English | MEDLINE | ID: covidwho-1415645

ABSTRACT

OBJECTIVE: To determine the incidence of influenza and noninfluenza respiratory viruses (NIRVs) pre-/post-implementation of public health measures aimed to decrease coronavirus disease 2019 (COVID-19) transmission using population-based surveillance data. We hypothesized that such measures could reduce the burden of respiratory viruses (RVs) transmitting via the same routes. PATIENTS AND METHODS: An interrupted time-series analysis of RV surveillance data in Alberta, Canada, from May 2017 to July 2020 was conducted. The burden of influenza and NIRVs before and after intervention initiation at week 11 was compared. The analysis was adjusted for seasonality, overdispersion, and autocorrelation. RESULTS: During the study period, an average of 708 and 4056 weekly respiratory multiplex molecular panels were conducted pre-/post-intervention, respectively. We found significant reductions in test positivity rates in the postintervention period for influenza (-94.3%; 95% CI, -93.8 to 97.4%; P<.001) and all NIRVs (-76.5%; 95% CI, -77.3 to -75.8%; P<.001) in the crude model, and -86.2% (95% CI, -91.5 to -77.4%: P<.001) and -75% (95% CI, -79.7 to -69.3%; P<.001), respectively, in the adjusted models. Subanalyses for individual viruses showed significant decreases in respiratory syncytial virus, human metapneumovirus, enterovirus/rhinovirus, and parainfluenza. For non-severe acute respiratory coronavirus 2 human coronaviruses, the decline was not statistically significant after adjustment (-22.3%; 95% CI, -49.3 to +19%, P=.246). CONCLUSION: The implementation of COVID-19 public health measures likely resulted in reduced transmission of common RVs. Although drastic lockdowns are unlikely to be required given widespread COVID-19 vaccination, targeted implementation of such measures can lower RV disease burden. Studies to evaluate relative contributions of individual interventions are warranted.


Subject(s)
COVID-19 , Communicable Disease Control , Disease Transmission, Infectious/prevention & control , Respiratory Tract Infections , Virus Diseases , Viruses , Adolescent , Adult , Aged , Alberta/epidemiology , COVID-19/epidemiology , COVID-19/prevention & control , Communicable Disease Control/methods , Communicable Disease Control/organization & administration , Communicable Disease Control/statistics & numerical data , Epidemiological Monitoring , Humans , Incidence , Infant, Newborn , Influenza, Human/epidemiology , Interrupted Time Series Analysis/statistics & numerical data , Public Health/methods , Public Health/statistics & numerical data , Respiratory Tract Infections/epidemiology , Respiratory Tract Infections/prevention & control , SARS-CoV-2 , Seasons , Virus Diseases/classification , Virus Diseases/epidemiology , Virus Diseases/prevention & control , Viruses/classification , Viruses/isolation & purification
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