Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India.
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ABSTRACT:
SUBMITTER: Ko S
PROVIDER: S-EPMC10242422 | biostudies-literature | 2023 Jun
REPOSITORIES: biostudies-literature
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Patterns in Child Health Outcomes Before and After the COVID-19 Outbreak in India.
Ko Soohyeon S Kim Rockli R Subramanian S V SV
JAMA network open 20230601 6
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Project description: Not available
| S-EPMC8824303 | biostudies-literature
Project description:Globally, restrictions implemented to limit the spread of COVID-19 have highlighted deeply rooted social divisions, raising concerns about differential impacts on members of different groups. Inequalities among households of different castes are ubiquitous in certain regions of India. Drawing on a novel data set of 8,564 households in Uttar Pradesh, the authors use radar plots to examine differences between castes in rates of activity for several typical behaviors before, during, and upon lifting strict lockdown restrictions. The visualization reveals that members of all castes experienced comparable reductions in activity rates during lockdown and recovery rates following it. Nonetheless, members of less privileged castes procure water outside the household more often than their more privileged peers, highlighting an avenue of improvement for future public health efforts.
| S-EPMC9393403 | biostudies-literature
Project description:To clarify the physical and mental conditions of children during the coronavirus disease 2019 pandemic and consequent social distancing in relation to the mental condition of their caregivers. This internet-based nationwide cross-sectional study was conducted between April 30 and May 13, 2020. The participants were 1,200 caregivers of children aged 3-14 years. Child health issues were categorized into "at least one" or "none" according to caregivers' perception. Caregivers' mental status was assessed using the Japanese version of the Kessler Psychological Distress Scale-6. The association between caregivers' mental status and child health issues was analyzed using logistic regression models. Among the participants, 289 (24.1%) had moderate and 352 (29.3%) had severe mental distress and 69.8% of children in their care had health issues. The number of caregivers with mental distress was more than double that reported during the 2016 national survey. After adjusting for covariates, child health issues increased among caregivers with moderate mental distress (odds ratio 2.24, 95% confidence interval 1.59-3.16) and severe mental distress (odds ratio 3.05, 95% confidence interval 2.17-4.29) compared with caregivers with no mental distress. The results highlight parents' psychological stress during the pandemic, suggesting the need for adequate parenting support. However, our study did not consider risk factors of caregivers' mental distress such as socioeconomic background. There is an urgent need for further research to identify vulnerable populations and children's needs to develop sustainable social support programs for those affected by the outbreak.
| S-EPMC7728265 | biostudies-literature
Project description:IntroductionThe outbreak of COVID-19 disrupted lives across the United States. Evidence shows that such a climate is deleterious to mental health and may increase demand for mental health services in emergency departments. The purpose of this study was to determine the difference in emergency department utilization for mental health diagnoses before and after the COVID-19 surge.MethodsWe conducted a cross-sectional study between January-August 2019 and January-August 2020 with emergency department encounter as the sampling unit. The primary outcome was the proportion of all emergency department encounters attributed to mental health. We performed chi-square analyses to evaluate the differences between 2019 and 2020.ResultsWe found that overall emergency department volume declined between 2019 and 2020, while the proportion attributable to mental health conditions increased (p < 0.01). Substance abuse, anxiety, and mood disorders accounted for nearly 90% of mental health diagnoses during both periods. When stratified by sex, substance abuse was the leading mental health diagnosis for males and anxiety and substance abuse disorders combined accounted for the largest proportion for females.DiscussionThe emergency department is an important community resource for the identification and triage of mental health emergencies. This role is even more important during disasters and extended crises, making it imperative that emergency departments employ experienced mental health staff. This study provides a comparison of emergency department utilization for mental health diagnoses before the pandemic and during the spring 2020 surge and may serve as a useful guide for hospitals, health systems and communities in future planning.
| S-EPMC8010358 | biostudies-literature
Project description:High throughput sequencing is performed on mRNA isolated from whole blood of adult Covid-19 patients, bacterial coinfection with Covid-19 and healthy controls in a South Indian cohort. Samples were collected from individuals at the time of hospitalization or visit to clinic. The Covid-19 samples are categorized by severeity.
2022-02-22 | GSE196822 | GEO
Project description:BackgroundThe World Health Organization declared COVID-19, the disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a global pandemic on March 11, 2020. Non-pharmaceutical interventions such as social distancing, handwashing, using hand sanitizer, and wearing facial masks are recommended as the first line of protection against COVID-19. Encouraging hand hygiene may be one of the most cost-effective means of reducing the global burden of disease.MethodsThis study uses a web-based questionnaire to evaluate the usage patterns and consumer perceptions of the effectiveness and health safety of bar soap, liquid hand soap, and hand sanitizer products before and after the spread of COVID-19.ResultsThe results show that since the outbreak of COVID-19, the number of consumers who primarily use bar soap has decreased from 71.8 to 51.4%, the number of those who primarily use liquid hand soap has increased from 23.5 to 41.3%, and the number of those who use and carry hand sanitizer has increased. The frequency of use, duration of use, and amount used of all three products have increased significantly since the COVID-19 outbreak. Finally, consumer perception of the products' preventive effect against COVID-19 is higher for liquid hand soap and hand sanitizer than it is for bar soap.ConclusionsBecause use of hand sanitizers has increased, public health guidelines must address the potential risks associated them. Our data also show that the public is abiding by the recommendations of the regulatory authorities. As handwashing has become important in preventing COVID-19 infections, the results of our study will support the development of better handwashing guidelines and a public health campaign.Supplementary informationThe online version contains supplementary material available at 10.1186/s12302-021-00517-8.
| S-EPMC8254429 | biostudies-literature
Project description:As the outbreak of coronavirus disease 2019 (COVID-19) is rapidly spreading in different parts of India, a reliable forecast for the cumulative confirmed cases and the number of deaths can be helpful for policymakers in making the decisions for utilizing available resources in the country. Recently, various mathematical models have been used to predict the outbreak of COVID-19 worldwide and also in India. In this article we use exponential, logistic, Gompertz growth and autoregressive integrated moving average (ARIMA) models to predict the spread of COVID-19 in India after the announcement of various unlock phases. The mean absolute percentage error and root mean square error comparative measures were used to check the goodness-of-fit of the growth models and Akaike information criterion for ARIMA model selection. Using COVID-19 pandemic data up to 20 December 2020 from India and its five most affected states (Maharashtra, Karnataka, Andhra Pradesh, Tamil Nadu and Kerala), we report 15-days-ahead forecasts for cumulative confirmed cases and the number of deaths. Based on available data, we found that the ARIMA model is the best-fitting model for COVID-19 cases in India and its most affected states.
| S-EPMC8194983 | biostudies-literature
Project description:The objective was to investigate the association between deprivation and COVID-19 outcomes in Italy during pre-lockdown, lockdown and post-lockdown periods using a retrospective cohort study with 38,534,169 citizens and 222,875 COVID-19 cases. Multilevel negative binomial regression models, adjusting for age, sex, population-density and region of residence were conducted to evaluate the association between area-level deprivation and COVID-19 incidence, case-hospitalisation rate and case-fatality. During lockdown and post-lockdown, but not during pre-lockdown, higher incidence of cases was observed in the most deprived municipalities compared with the least deprived ones. No differences in case-hospitalisation and case-fatality according to deprivation were observed in any period under study.
| S-EPMC8318679 | biostudies-literature
Project description:BackgroundMobile health (mHealth) apps are rapidly emerging technologies in China due to strictly controlled medical needs during the COVID-19 pandemic while continuing essential services for chronic diseases. However, there have been no large-scale, systematic efforts to evaluate relevant apps.ObjectiveWe aim to provide a landscape of mHealth apps in China by describing and comparing digital health concerns before and after the COVID-19 outbreak, including mHealth app data flow and user experience, and analyze the impact of COVID-19 on mHealth apps.MethodsWe conducted a semilongitudinal survey of 1593 mHealth apps to study the app data flow and clarify usage changes and influencing factors. We selected mHealth apps in app markets, web pages from the Baidu search engine, the 2018 top 100 hospitals with internet hospitals, and online shopping sites with apps that connect to smart devices. For user experience, we recruited residents from a community in southeastern China from October 2019 to November 2019 (before the outbreak) and from June 2020 to August 2020 (after the outbreak) comparing the attention of the population to apps. We also examined associations between app characteristics, functions, and outcomes at specific quantiles of distribution in download changes using quantile regression models.ResultsRehabilitation medical support was the top-ranked functionality, with a median 1.44 million downloads per app prepandemic and a median 2.74 million downloads per app postpandemic. Among the top 10 functions postpandemic, 4 were related to maternal and child health: pregnancy preparation (ranked second; fold change 4.13), women's health (ranked fifth; fold change 5.16), pregnancy (ranked sixth; fold change 5.78), and parenting (ranked tenth; fold change 4.03). Quantile regression models showed that rehabilitation (P75, P90), pregnancy preparation (P90), bodybuilding (P50, P90), and vaccination (P75) were positively associated with an increase in downloads after the outbreak. In the user experience survey, the attention given to health information (prepandemic: 249/375, 66.4%; postpandemic: 146/178, 82.0%; P=.006) steadily increased after the outbreak.ConclusionsmHealth apps are an effective health care approach gaining in popularity among the Chinese population following the COVID-19 outbreak. This research provides direction for subsequent mHealth app development and promotion in the postepidemic era, supporting medical model reformation in China as a reference, which may provide new avenues for designing and evaluating indirect public health interventions such as health education and health promotion.
| S-EPMC9996426 | biostudies-literature