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2.
Front Biosci (Elite Ed) ; 13(2): 272-290, 2021 12 20.
Article in English | MEDLINE | ID: covidwho-1591755

ABSTRACT

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a lethal virus that was detected back on 31st December 2019 in Wuhan, Hubei province in China, and since then this virus has been spreading across the globe causing a global outbreak and has left the world fighting against the virus. The disease caused by the SARS-CoV-2 was named COVID-19 and this was declared a pandemic disease by the World Health Organization on 11th March 2020. Several nations are trying to develop a vaccine that can save millions of lives. This review outlines the morphological features of the virus describing the outer and inner structures of the virus along with the entry mechanism of the virus into the host body and the infection process. Detailed reports of global outbreak along with preventive measures have also been included, with special emphasis on China, the United States of America, India, Italy, and South Korea. Broad-spectrum antiviral drugs being used at various health care centres around the world, namely Remdesivir, Camostat & Nafamostat, Famotidine, Chloroquine & Hydroxychloroquine, Lopinavir/ritonavir, Ivermectin, and Tocilizumab & Sarilumab have also been included. World Health Organization guidelines on preventive measures and use of soaps, alcohol-based hand-rubs and wearing face masks have also been described. The vaccines that are in one of the phases of human trials, namely Oxford University's vaccine, the United States-based Moderna's vaccine, India's Covaxin and the Russian vaccine, have also been incorporated in the review article.


Subject(s)
Antiviral Agents/therapeutic use , COVID-19 Vaccines , COVID-19/drug therapy , COVID-19/prevention & control , SARS-CoV-2/physiology , SARS-CoV-2/pathogenicity , Animals , Antiviral Agents/pharmacology , COVID-19/epidemiology , COVID-19/virology , Humans , Pandemics/prevention & control , Pandemics/statistics & numerical data , SARS-CoV-2/drug effects
3.
PLoS One ; 16(12): e0261321, 2021.
Article in English | MEDLINE | ID: covidwho-1581753

ABSTRACT

By September 2020, COVID-19 had claimed the lives of almost 1 million people worldwide, including more than 400,000 in the U.S. and Europe [1] To slow the spread of the virus, health officials advised social distancing, regular handwashing, and wearing a face covering [2]. We hypothesized that public adherence to the health guidance would be influenced by prevailing social norms, and the prevalence of these behaviors among others. We focused on mask-wearing behavior during fall 2020, and coded livestream public webcam footage of 1,200 individuals across seven cities. Results showed that only 50% of participants were correctly wearing a mask in public, and that this percentage varied as a function of the mask-wearing behavior of close and distant others in the immediate physical vicinity. How social normative information might be used to increase mask-wearing behavior is discussed. "Cloth face coverings are one of the most powerful weapons we have to slow and stop the spread of the virus-particularly when used universally within a community setting" CDC Director Dr. Robert Redfield in July 2020.


Subject(s)
COVID-19 , Masks/statistics & numerical data , Pandemics/statistics & numerical data , Social Behavior , Adult , COVID-19/epidemiology , COVID-19/psychology , Female , Humans , Male , Middle Aged
4.
Biomed Environ Sci ; 34(11): 871-880, 2021 Nov 20.
Article in English | MEDLINE | ID: covidwho-1580280

ABSTRACT

Objective: Previous studies have shown that meteorological factors may increase COVID-19 mortality, likely due to the increased transmission of the virus. However, this could also be related to an increased infection fatality rate (IFR). We investigated the association between meteorological factors (temperature, humidity, solar irradiance, pressure, wind, precipitation, cloud coverage) and IFR across Spanish provinces ( n = 52) during the first wave of the pandemic (weeks 10-16 of 2020). Methods: We estimated IFR as excess deaths (the gap between observed and expected deaths, considering COVID-19-unrelated deaths prevented by lockdown measures) divided by the number of infections (SARS-CoV-2 seropositive individuals plus excess deaths) and conducted Spearman correlations between meteorological factors and IFR across the provinces. Results: We estimated 2,418,250 infections and 43,237 deaths. The IFR was 0.03% in < 50-year-old, 0.22% in 50-59-year-old, 0.9% in 60-69-year-old, 3.3% in 70-79-year-old, 12.6% in 80-89-year-old, and 26.5% in ≥ 90-year-old. We did not find statistically significant relationships between meteorological factors and adjusted IFR. However, we found strong relationships between low temperature and unadjusted IFR, likely due to Spain's colder provinces' aging population. Conclusion: The association between meteorological factors and adjusted COVID-19 IFR is unclear. Neglecting age differences or ignoring COVID-19-unrelated deaths may severely bias COVID-19 epidemiological analyses.


Subject(s)
COVID-19/epidemiology , Pandemics/statistics & numerical data , Weather , Adult , Aged , Aged, 80 and over , COVID-19/virology , Humans , Meteorological Concepts , Middle Aged , SARS-CoV-2/physiology , Spain/epidemiology , Young Adult
5.
PLoS One ; 16(11): e0259097, 2021.
Article in English | MEDLINE | ID: covidwho-1575776

ABSTRACT

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) poses a high risk of transmission in close-contact indoor settings, which may include households. Prior studies have found a wide range of household secondary attack rates and may contain biases due to simplifying assumptions about transmission variability and test accuracy. METHODS: We compiled serological SARS-CoV-2 antibody test data and prior SARS-CoV-2 test reporting from members of 9,224 Utah households. We paired these data with a probabilistic model of household importation and transmission. We calculated a maximum likelihood estimate of the importation probability, mean and variability of household transmission probability, and sensitivity and specificity of test data. Given our household transmission estimates, we estimated the threshold of non-household transmission required for epidemic growth in the population. RESULTS: We estimated that individuals in our study households had a 0.41% (95% CI 0.32%- 0.51%) chance of acquiring SARS-CoV-2 infection outside their household. Our household secondary attack rate estimate was 36% (27%- 48%), substantially higher than the crude estimate of 16% unadjusted for imperfect serological test specificity and other factors. We found evidence for high variability in individual transmissibility, with higher probability of no transmissions or many transmissions compared to standard models. With household transmission at our estimates, the average number of non-household transmissions per case must be kept below 0.41 (0.33-0.52) to avoid continued growth of the pandemic in Utah. CONCLUSIONS: Our findings suggest that crude estimates of household secondary attack rate based on serology data without accounting for false positive tests may underestimate the true average transmissibility, even when test specificity is high. Our finding of potential high variability (overdispersion) in transmissibility of infected individuals is consistent with characterizing SARS-CoV-2 transmission being largely driven by superspreading from a minority of infected individuals. Mitigation efforts targeting large households and other locations where many people congregate indoors might curb continued spread of the virus.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Family Characteristics , Humans , Incidence , Likelihood Functions , Pandemics/statistics & numerical data , SARS-CoV-2/pathogenicity , Sensitivity and Specificity , Serologic Tests/methods , Utah/epidemiology
6.
PLoS One ; 16(3): e0248627, 2021.
Article in English | MEDLINE | ID: covidwho-1575736

ABSTRACT

BACKGROUND: There has been a rapid increase in the number of cases of COVID-19 in Latin America, Africa, Asia and many countries that have an insufficient number of physicians and other health care personnel, and the need for the inclusion of medical students on health teams is a very important issue. It has been recommended that medical students work as volunteers, undergo appropriate training, not undertake any activity beyond their level of competence, and receive continuous supervision and adequate personal protective equipment. However, the motivation of medical students must be evaluated to make volunteering a more evidence-based initiative. The aim of our study was to evaluate the motivation of medical students to be part of health teams to aid in the COVID-19 pandemic. METHODS AND FINDINGS: We developed a questionnaire specifically to evaluate medical students' perceptions about participating in the care of patients with suspected infection with coronavirus during the COVID-19 pandemic. The questionnaire had two parts: a) one part with questions on individual characteristics, year in medical school and geographic location of the medical school and b) a second part with twenty-eight statements assessed on a 5-point Likert scale (totally agree, agree, neither agree nor disagree, disagree and totally disagree). To develop the questionnaire, we performed consensus meetings with a group of faculty and medical students. The questionnaire was sent to student organizations of 257 medical schools in Brazil and answered by 10,433 students. We used multinomial logistic regression models to analyze the data. Statements associated with greater odds ratios for participation of medical students in the COVID-19 pandemic were related to a sense of purpose or duty ("It is the duty of the medical student to put himself or herself at the service of the population in the pandemic"), altruism ("I am willing to take risks by participating in practice in the context of the pandemic"), and perception of good performance and professional identity ("I will be a better health professional for having experienced the pandemic"). Males were more prone than females to believe that only interns should participate in the care of patients with COVID-19 (odds ratio 1.36 [coefficient interval 95%:1.24-1.49]) and that all students should participate (OR 1.68 [CI:1.4-1.91]). CONCLUSIONS: Medical students are more motivated by a sense of purpose or duty, altruism, perception of good performance and values of professionalism than by their interest in learning. These results have implications for the development of volunteering programs and the design of health force policies in the present pandemic and in future health emergencies.


Subject(s)
COVID-19/psychology , Pandemics/statistics & numerical data , Schools, Medical/statistics & numerical data , Students, Medical/psychology , Students, Medical/statistics & numerical data , Attitude of Health Personnel , COVID-19/prevention & control , Female , Health Personnel/psychology , Health Personnel/statistics & numerical data , Humans , Male , Motivation/physiology , Pandemics/prevention & control , Perception/physiology , SARS-CoV-2/pathogenicity , Surveys and Questionnaires
7.
PLoS One ; 16(3): e0247993, 2021.
Article in English | MEDLINE | ID: covidwho-1574098

ABSTRACT

Population ageing requires society to adjust by ensuring additional types of services and assistance for elderly people. These may be provided by either organized services and sources of informal social support. The latter are especially important since a lack of social support is associated with a lower level of psychological and physical well-being. During the Covid-19 pandemic, social support for the elderly has proven to be even more crucial, also due to physical distancing. Therefore, this study aims to identify and describe the various types of personal social support networks available to the elderly population during the pandemic. To this end, a survey of Slovenians older than 64 years was conducted from April 25 to May 4, 2020 on a probability web-panel-based sample (n = 605). The ego networks were clustered by a hierarchical clustering approach for symbolic data. Clustering was performed for different types of social support (socializing, instrumental support, emotional support) and different characteristics of the social support networks (i.e., type of relationship, number of contacts, geographical distance). The results show that most of the elderly population in Slovenia has a satisfactory social support network, while the share of those without any (accessible) source of social support is significant. The results are particularly valuable for sustainable care policy planning, crisis intervention planning as well as any future waves of the coronavirus.


Subject(s)
COVID-19/psychology , Psychosocial Support Systems , Social Support , Aged , Aged, 80 and over , Aging , COVID-19/epidemiology , Coronavirus Infections/epidemiology , Female , Humans , Male , Pandemics/statistics & numerical data , SARS-CoV-2/pathogenicity , Slovenia/epidemiology , Surveys and Questionnaires
8.
PLoS One ; 16(3): e0248072, 2021.
Article in English | MEDLINE | ID: covidwho-1573852

ABSTRACT

The spread of COVID-19 and resulting local and national lockdowns have a host of potential consequences for demographic trends. While impacts on mortality and, to some extent, short-term migration flows are beginning to be documented, it is too early to measure actual consequences for family demography. To gain insight into potential future consequences of the lockdown for family demography, we use cross-national Google Trends search data to explore whether trends in searches for words related to fertility, relationship formation, and relationship dissolution changed following lockdowns compared to average, pre-lockdown levels in Europe and the United States. Because lockdowns were not widely anticipated or simultaneous in timing or intensity, we exploit variability over time and between countries (and U.S. states). We use a panel event-study design and difference-in-differences methods, and account for seasonal trends and average country-level (or state-level) differences in searches. We find statistically significant impacts of lockdown timing on changes in searches for terms such as wedding and those related to condom use, emergency contraception, pregnancy tests, and abortion, but little evidence of changes in searches related to fertility. Impacts for union formation and dissolution tended to only be statistically significant at the start of a lockdown with a return to average-levels about 2 to 3 months after lockdown initiation, particularly in Europe. Compared to Europe, returns to average search levels were less evident for the U.S., even 2 to 3 months after lockdowns were introduced. This may be due to the fact, in the U.S., health and social policy responses were less demarcated than in Europe, such that economic uncertainty was likely of larger magnitude. Such pandemic-related economic uncertainty may therefore have the potential to slightly increase already existing polarization in family formation behaviours in the U.S. Alongside contributing to the wider literature on economic uncertainty and family behaviors, this paper also proposes strategies for efficient use of Google Trends data, such as making relative comparisons and testing sensitivity to outliers, and provides a template and cautions for their use in demographic research when actual demographic trends data are not yet available.


Subject(s)
COVID-19/psychology , Pandemics/statistics & numerical data , COVID-19/prevention & control , Europe , Family Characteristics , Humans , Pandemics/prevention & control , Public Policy , Quarantine/psychology , Quarantine/statistics & numerical data , SARS-CoV-2/pathogenicity , United States
9.
PLoS Comput Biol ; 17(12): e1009697, 2021 12.
Article in English | MEDLINE | ID: covidwho-1571974

ABSTRACT

For the control of COVID-19, vaccination programmes provide a long-term solution. The amount of available vaccines is often limited, and thus it is crucial to determine the allocation strategy. While mathematical modelling approaches have been used to find an optimal distribution of vaccines, there is an excessively large number of possible allocation schemes to be simulated. Here, we propose an algorithm to find a near-optimal allocation scheme given an intervention objective such as minimization of new infections, hospitalizations, or deaths, where multiple vaccines are available. The proposed principle for allocating vaccines is to target subgroups with the largest reduction in the outcome of interest. We use an approximation method to reconstruct the age-specific transmission intensity (the next generation matrix), and express the expected impact of vaccinating each subgroup in terms of the observed incidence of infection and force of infection. The proposed approach is firstly evaluated with a simulated epidemic and then applied to the epidemiological data on COVID-19 in the Netherlands. Our results reveal how the optimal allocation depends on the objective of infection control. In the case of COVID-19, if we wish to minimize deaths, the optimal allocation strategy is not efficient for minimizing other outcomes, such as infections. In simulated epidemics, an allocation strategy optimized for an outcome outperforms other strategies such as the allocation from young to old, from old to young, and at random. Our simulations clarify that the current policy in the Netherlands (i.e., allocation from old to young) was concordant with the allocation scheme that minimizes deaths. The proposed method provides an optimal allocation scheme, given routine surveillance data that reflect ongoing transmissions. This approach to allocation is useful for providing plausible simulation scenarios for complex models, which give a more robust basis to determine intervention strategies.


Subject(s)
Algorithms , COVID-19 Vaccines/therapeutic use , COVID-19/prevention & control , SARS-CoV-2 , Vaccination/methods , Age Factors , COVID-19/epidemiology , COVID-19/immunology , COVID-19 Vaccines/supply & distribution , Computational Biology , Computer Simulation , Health Care Rationing/methods , Health Care Rationing/statistics & numerical data , Humans , Mass Vaccination/methods , Mass Vaccination/statistics & numerical data , Netherlands/epidemiology , Pandemics/prevention & control , Pandemics/statistics & numerical data , SARS-CoV-2/immunology , Vaccination/statistics & numerical data
10.
Proc Natl Acad Sci U S A ; 118(51)2021 12 21.
Article in English | MEDLINE | ID: covidwho-1569348

ABSTRACT

Simultaneously tracking the global impact of COVID-19 is challenging because of regional variation in resources and reporting. Leveraging self-reported survey outcomes via an existing international social media network has the potential to provide standardized data streams to support monitoring and decision-making worldwide, in real time, and with limited local resources. The University of Maryland Global COVID-19 Trends and Impact Survey (UMD-CTIS), in partnership with Facebook, has invited daily cross-sectional samples from the social media platform's active users to participate in the survey since its launch on April 23, 2020. We analyzed UMD-CTIS survey data through December 20, 2020, from 31,142,582 responses representing 114 countries/territories weighted for nonresponse and adjusted to basic demographics. We show consistent respondent demographics over time for many countries/territories. Machine Learning models trained on national and pooled global data verified known symptom indicators. COVID-like illness (CLI) signals were correlated with government benchmark data. Importantly, the best benchmarked UMD-CTIS signal uses a single survey item whereby respondents report on CLI in their local community. In regions with strained health infrastructure but active social media users, we show it is possible to define COVID-19 impact trajectories using a remote platform independent of local government resources. This syndromic surveillance public health tool is the largest global health survey to date and, with brief participant engagement, can provide meaningful, timely insights into the global COVID-19 pandemic at a local scale.


Subject(s)
COVID-19/epidemiology , Public Health Surveillance/methods , Social Media , COVID-19/diagnosis , COVID-19 Testing , Cross-Sectional Studies , Epidemiologic Methods , Humans , Internationality , Machine Learning , Pandemics/statistics & numerical data
12.
J Med Virol ; 93(12): 6628-6633, 2021 12.
Article in English | MEDLINE | ID: covidwho-1544311

ABSTRACT

As the emergence of new variants of SARS-CoV-2 persists across the world, it is of importance to understand the distributional behavior of the incubation period of the variants for both medical research and public health policy-making. We collected the published individual-level data of 941 patients of the 2020-2021 winter pandemic wave in Hebei province, North China. We computed some epidemiological characteristics of the wave and estimated the distribution of the incubation period. We further assessed the covariate effects of sex, age, and living with a case with respect to the incubation period by a model. The infection-fatality rate was only 0.1%. The estimated median incubation period was at least 22 days, significantly extended from the estimates (ranging from 4 to 8.5 days) of the previous wave in mainland China and those ever reported elsewhere around the world. The proportion of asymptomatic patients was 90.6%. No significant covariate effect was found. The distribution of incubation period of the new variants showed a clear extension from their early generations.


Subject(s)
COVID-19/epidemiology , Infectious Disease Incubation Period , SARS-CoV-2/physiology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/virology , Child , Child, Preschool , China/epidemiology , Female , Humans , Kaplan-Meier Estimate , Male , Middle Aged , Pandemics/statistics & numerical data , Young Adult
13.
J Am Coll Radiol ; 17(8): 1011-1013, 2020 08.
Article in English | MEDLINE | ID: covidwho-1536620

ABSTRACT

BACKGROUND: Quarantine and stay-at-home orders are strategies that many countries used during the acute pandemic period of coronavirus disease 2019 (COVID-19) to prevent disease dissemination, health system overload, and mortality. However, there are concerns that patients did not seek necessary health care because of these mandates. PURPOSE: To evaluate the differences in the clinical presentation of acute appendicitis and CT findings related to these cases between the COVID-19 acute pandemic period and nonpandemic period. MATERIALS AND METHODS: A retrospective observational study was performed to compare the acute pandemic period (March 23, 2020, to May 4, 2020) versus the same period the year before (March 23, 2019, to May 4, 2019). The proportion of appendicitis diagnosed by CT and level of severity of the disease were reviewed in each case. Univariate and bivariate analyses were performed to identify significant differences between the two groups. RESULTS: A total of 196 abdominal CT scans performed due to suspected acute appendicitis were evaluated: 55 from the acute pandemic period and 141 from the nonpandemic period. The proportion of acute appendicitis diagnosed by abdominal CT was higher in the acute pandemic period versus the nonpandemic period: 45.5% versus 29.8% (P = .038). The severity of the diagnosed appendicitis was higher during the acute pandemic period: 92% versus 57.1% (P = .003). CONCLUSION: During the acute COVID-19 pandemic period, fewer patients presented with acute appendicitis to the emergency room, and those who did presented at a more severe stage of the disease.


Subject(s)
Appendicitis/diagnostic imaging , Appendicitis/epidemiology , Coronavirus Infections/prevention & control , Infection Control/organization & administration , Pandemics/prevention & control , Pneumonia, Viral/prevention & control , Tomography, X-Ray Computed/statistics & numerical data , Analysis of Variance , COVID-19 , Cohort Studies , Coronavirus Infections/epidemiology , Emergency Service, Hospital/statistics & numerical data , Female , Humans , Incidence , Male , Multivariate Analysis , Pandemics/statistics & numerical data , Pneumonia, Viral/epidemiology , Quarantine/statistics & numerical data , Retrospective Studies , Risk Assessment , Tomography, X-Ray Computed/methods , United States
14.
Sci Rep ; 11(1): 20121, 2021 10 11.
Article in English | MEDLINE | ID: covidwho-1532138

ABSTRACT

The Brazilian strategy to overcome the spread of COVID-19 has been particularly criticized due to the lack of a national coordinating effort and an appropriate testing program. Here, a successful approach to control the spread of COVID-19 transmission is described by the engagement of public (university and governance) and private sectors (hospitals and oil companies) in Macaé, state of Rio de Janeiro, Brazil, a city known as the National Oil Capital. In 2020 between the 17th and 38th epidemiological week, over two percent of the 206,728 citizens were subjected to symptom analysis and RT-qPCR testing by the Federal University of Rio de Janeiro, with positive individuals being notified up to 48 h after swab collection. Geocodification and spatial cluster analysis were used to limit COVID-19 spreading in Macaé. Within the first semester after the outbreak of COVID-19 in Brazil, Macaé recorded 1.8% of fatalities associated with COVID-19 up to the 38th epidemiological week, which was at least five times lower than the state capital (10.6%). Overall, considering the successful experience of this joint effort of private and public engagement in Macaé, our data suggest that the development of a similar strategy countrywise could have contributed to a better control of the COVID-19 spread in Brazil. Quarantine decree by the local administration, comprehensive molecular testing coupled to scientific analysis of COVID-19 spreading, prevented the catastrophic consequences of the pandemic as seen in other populous cities within the state of Rio de Janeiro and elsewhere in Brazil.


Subject(s)
COVID-19 Nucleic Acid Testing/statistics & numerical data , COVID-19/epidemiology , Pandemics/statistics & numerical data , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , Brazil/epidemiology , COVID-19/diagnosis , COVID-19/transmission , COVID-19/virology , Cities/epidemiology , Cities/statistics & numerical data , Female , Humans , Male , Middle Aged , RNA, Viral/isolation & purification , SARS-CoV-2/genetics , Young Adult
15.
Pediatr Nephrol ; 36(9): 2627-2638, 2021 09.
Article in English | MEDLINE | ID: covidwho-1520348

ABSTRACT

BACKGROUND AND OBJECTIVES: COVID-19 is responsible for the 2019 novel coronavirus disease pandemic. Despite the vast research about the adult population, there has been little data collected on acute kidney injury (AKI) epidemiology, associated risk factors, treatments, and mortality in pediatric COVID-19 patients admitted to the ICU. AKI is a severe complication of COVID-19 among children and adolescents. METHODS: A comprehensive literature search was conducted in PubMed/MEDLINE and Cochrane Center Trials to find all published literature related to AKI in COVID-19 patients, including incidence and outcomes. RESULTS: Twenty-four studies reporting the outcomes of interest were included. Across all studies, the overall sample size of COVID positive children was 1,247 and the median age of this population was 9.1 years old. Among COVID positive pediatric patients, there was an AKI incidence of 30.51%, with only 0.56% of these patients receiving KRT. The mortality was 2.55% among all COVID positive pediatric patients. The incidence of multisystem inflammatory syndrome in children (MIS-C) among COVID positive patients was 74.29%. CONCLUSION: AKI has shown to be a negative prognostic factor in adult patients with COVID-19 and now also in the pediatric cohort with high incidence and mortality rates. Additionally, our findings show a strong comparison in epidemiology between adult and pediatric COVID-19 patients; however, they need to be confirmed with additional data and studies.


Subject(s)
Acute Kidney Injury/epidemiology , COVID-19/complications , Intensive Care Units/statistics & numerical data , Renal Replacement Therapy/statistics & numerical data , Systemic Inflammatory Response Syndrome/complications , Acute Kidney Injury/immunology , Acute Kidney Injury/therapy , Acute Kidney Injury/virology , Adult , Age Factors , COVID-19/diagnosis , COVID-19/immunology , COVID-19/mortality , Child , Hospital Mortality , Humans , Incidence , Pandemics/statistics & numerical data , Risk Factors , SARS-CoV-2/isolation & purification , SARS-CoV-2/pathogenicity , Systemic Inflammatory Response Syndrome/diagnosis , Systemic Inflammatory Response Syndrome/immunology , Systemic Inflammatory Response Syndrome/mortality
16.
CMAJ Open ; 9(4): E988-E997, 2021.
Article in English | MEDLINE | ID: covidwho-1524571

ABSTRACT

BACKGROUND: The extent to which heightened distress during the COVID-19 pandemic translated to increases in severe mental health outcomes is unknown. We examined trends in psychiatric presentations to acute care settings in the first 12 months after onset of the pandemic. METHODS: This was a trends analysis of administrative population data in Ontario, Canada. We examined rates of hospitalizations and emergency department visits for mental health diagnoses overall and stratified by sex, age and diagnostic grouping (e.g., mood disorders, anxiety disorders, psychotic disorders), as well as visits for intentional self-injury for people aged 10 to 105 years, from January 2019 to March 2021. We used Joinpoint regression to identify significant inflection points after the onset of the pandemic in March 2020. RESULTS: Among the 12 968 100 people included in our analysis, rates of mental health-related hospitalizations and emergency department visits declined immediately after the onset of the pandemic (peak overall decline of 30% [hospitalizations] and 37% [emergency department visits] compared to April 2019) and returned to near prepandemic levels by March 2021. Compared to April 2019, visits for intentional self-injury declined by 33% and remained below prepandemic levels until March 2021. We observed the largest declines in service use among adolescents aged 14 to 17 years (55% decline in hospitalizations, 58% decline in emergency department visits) and 10 to 13 years (56% decline in self-injury), and for those with substance-related disorders (33% decline in emergency department visits) and anxiety disorders (61% decline in hospitalizations). INTERPRETATION: Contrary to expectations, the abrupt decline in acute mental health service use immediately after the onset of the pandemic and the return to near prepandemic levels that we observed suggest that changes and stressors in the first 12 months of the pandemic did not translate to increased service use. Continued surveillance of acute mental health service use is warranted.


Subject(s)
COVID-19/epidemiology , Mental Health Services/statistics & numerical data , Mental Health Services/trends , Pandemics/statistics & numerical data , Adolescent , Adult , Aged , Aged, 80 and over , Anxiety Disorders/epidemiology , Child , Emergency Service, Hospital/statistics & numerical data , Female , Hospitalization/statistics & numerical data , Humans , Male , Middle Aged , Mood Disorders/epidemiology , Ontario/epidemiology , Psychotic Disorders/epidemiology , SARS-CoV-2 , Self-Injurious Behavior/epidemiology , Substance-Related Disorders/epidemiology , Young Adult
17.
PLoS One ; 16(11): e0260310, 2021.
Article in English | MEDLINE | ID: covidwho-1523457

ABSTRACT

The first case of COVID-19 was detected in North Carolina (NC) on March 3, 2020. By the end of April, the number of confirmed cases had soared to over 10,000. NC health systems faced intense strain to support surging intensive care unit admissions and avert hospital capacity and resource saturation. Forecasting techniques can be used to provide public health decision makers with reliable data needed to better prepare for and respond to public health crises. Hospitalization forecasts in particular play an important role in informing pandemic planning and resource allocation. These forecasts are only relevant, however, when they are accurate, made available quickly, and updated frequently. To support the pressing need for reliable COVID-19 data, RTI adapted a previously developed geospatially explicit healthcare facility network model to predict COVID-19's impact on healthcare resources and capacity in NC. The model adaptation was an iterative process requiring constant evolution to meet stakeholder needs and inform epidemic progression in NC. Here we describe key steps taken, challenges faced, and lessons learned from adapting and implementing our COVID-19 model and coordinating with university, state, and federal partners to combat the COVID-19 epidemic in NC.


Subject(s)
COVID-19/epidemiology , Hospital Bed Capacity/statistics & numerical data , Hospitalization/trends , Intensive Care Units/trends , Pandemics/statistics & numerical data , Delivery of Health Care , Forecasting , Humans , North Carolina/epidemiology
18.
PLoS One ; 16(11): e0260061, 2021.
Article in English | MEDLINE | ID: covidwho-1523450

ABSTRACT

Here, we sought to quantify the effects of experienced fear and worry, engendered by the COVID-19 pandemic, on both cognitive abilities-speed of information processing, task-set shifting, and proactive control-as well as economic risk-taking. Leveraging a repeated-measures cross-sectional design, we examined the performance of 1517 participants, collected during the early phase of the pandemic in the US (April-June 2020), finding that self-reported pandemic-related worry predicted deficits in information processing speed and maintenance of goal-related contextual information. In a classic economic risk-taking task, we observed that worried individuals' choices were more sensitive to the described outcome probabilities of risky actions. Overall, these results elucidate the cognitive consequences of a large-scale, unpredictable, and uncontrollable stressor, which may in turn play an important role in individuals' understanding of, and adherence to safety directives both in the current crisis and future public health emergencies.


Subject(s)
Anxiety , COVID-19/psychology , Cognition , Fear , Pandemics/statistics & numerical data , Adult , Child , Cross-Sectional Studies , Female , Humans , Male , Surveys and Questionnaires
19.
PLoS One ; 16(11): e0258893, 2021.
Article in English | MEDLINE | ID: covidwho-1511820

ABSTRACT

OBJECTIVE: Explore how previous work during the 2003 Severe Acute Respiratory Syndrome (SARS) outbreak affects the psychological response of clinical and non-clinical healthcare workers (HCWs) to the current COVID-19 pandemic. METHODS: A cross-sectional, multi-centered hospital online survey of HCWs in the Greater Toronto Area, Canada. Mental health outcomes of HCWs who worked during the COVID-19 pandemic and the SARS outbreak were assessed using Impact of Events-Revised scale (IES-R), Generalized Anxiety Disorder scale (GAD-7), and Patient Health Questionnaire (PHQ-9). RESULTS: Among 3852 participants, moderate/severe scores for symptoms of post- traumatic stress disorder (PTSD) (50.2%), anxiety (24.6%), and depression (31.5%) were observed among HCWs. Work during the 2003 SARS outbreak was reported by 1116 respondents (29.1%), who had lower scores for symptoms of PTSD (P = .002), anxiety (P < .001), and depression (P < .001) compared to those who had not worked during the SARS outbreak. Multivariable logistic regression analysis showed non-clinical HCWs during this pandemic were at higher risk of anxiety (OR, 1.68; 95% CI, 1.19-2.15, P = .01) and depressive symptoms (OR, 2.03; 95% CI, 1.34-3.07, P < .001). HCWs using sedatives (OR, 2.55; 95% CI, 1.61-4.03, P < .001), those who cared for only 2-5 patients with COVID-19 (OR, 1.59; 95% CI, 1.06-2.38, P = .01), and those who had been in isolation for COVID-19 (OR, 1.36; 95% CI, 0.96-1.93, P = .05), were at higher risk of moderate/severe symptoms of PTSD. In addition, deterioration in sleep was associated with symptoms of PTSD (OR, 4.68, 95% CI, 3.74-6.30, P < .001), anxiety (OR, 3.09, 95% CI, 2.11-4.53, P < .001), and depression (OR 5.07, 95% CI, 3.48-7.39, P < .001). CONCLUSION: Psychological distress was observed in both clinical and non-clinical HCWs, with no impact from previous SARS work experience. As the pandemic continues, increasing psychological and team support may decrease the mental health impacts.


Subject(s)
COVID-19/epidemiology , COVID-19/psychology , Health Personnel/psychology , Severe Acute Respiratory Syndrome/epidemiology , Severe Acute Respiratory Syndrome/psychology , Adaptation, Psychological/physiology , Adolescent , Adult , Allied Health Personnel , Anxiety/psychology , Anxiety/virology , Anxiety Disorders/psychology , Anxiety Disorders/virology , COVID-19/virology , Canada , Cross-Sectional Studies , Depression/psychology , Depression/virology , Disease Outbreaks , Female , Humans , Male , Mental Health , Middle Aged , Outcome Assessment, Health Care , Pandemics/statistics & numerical data , Patient Health Questionnaire , Psychological Distress , SARS-CoV-2/pathogenicity , Severe Acute Respiratory Syndrome/virology , Stress Disorders, Post-Traumatic/psychology , Stress Disorders, Post-Traumatic/virology , Surveys and Questionnaires , Young Adult
20.
PLoS One ; 16(11): e0259454, 2021.
Article in English | MEDLINE | ID: covidwho-1506294

ABSTRACT

BACKGROUND: The COVID-19 pandemic seems to have a different picture in Africa; the first case was identified in the continent after it had already caused a significant loss to the rest of the world and the reported number of cases and mortality rate has been low. Understanding the characteristics and outcome of the pandemic in the African setup is therefore crucial. AIM: To assess the characteristics and outcome of Patients with COVID-19 and to identify determinants of the disease outcome among patients admitted to Millennium COVID-19 Care Center in Ethiopia. METHODS: A prospective cohort study was conducted among 1345 consecutively admitted RT-PCR confirmed Patients with COVID-19 from July to September, 2020. Frequency tables, KM plots, median survival times and Log-rank test were used to describe the data and compare survival distribution between groups. Cox proportional hazard survival model was used to identify determinants of time to clinical recovery and the independent variables, where adjusted hazard ratio, P-value and 95% CI for adjusted hazard ratio were used for testing significance and interpretation of results. Binary logistic regression model was used to assess the presence of a statistically significant association between disease outcome and the independent variables, where adjusted odds ratio, P-value and 95% CI for adjusted odds ratio were used for testing significance and interpretation of results. RESULTS: Among the study population, 71 (5.3%) died, 72 (5.4%) were transferred and the rest 1202 (89.4%) were clinically improved. The median time to clinical recovery was 14 days. On the multivariable Cox proportional hazard model; temperature (AHR = 1.135, 95% CI = 1.011, 1.274, p-value = 0.032), COVID-19 severity (AHR = 0.660, 95% CI = 0.501, 0.869, p-value = 0.003), and cough (AHR = 0.705, 95% CI = 0.519, 0.959, p-value = 0.026) were found to be significant determinants of time to clinical recovery. On the binary logistic regression, the following factors were found to be significantly associated with disease outcome; SPO2 (AOR = 0.302, 95% CI = 0.193, 0.474, p-value = 0.0001), shortness of breath (AOR = 0.354, 95% CI = 0.213, 0.590, p-value = 0.0001) and diabetes mellitus (AOR = 0.549, 95% CI = 0.337, 0.894, p-value = 0.016). CONCLUSIONS: The average duration of time to clinical recovery was 14 days and 89.4% of the patients achieved clinical recovery. The mortality rate of the studied population is lower than reports from other countries including those in Africa. Having severe COVID-19 disease severity and presenting with cough were found to be associated with delayed clinical recovery of the disease. On the other hand, being hyperthermic is associated with shorter disease duration (faster time to clinical recovery). In addition, lower oxygen saturation, subjective complaint of shortness of breath and being diabetic were associated with unfavorable disease outcome. Therefore, patients with these factors should be followed cautiously for a better outcome.


Subject(s)
COVID-19/epidemiology , Hospitalization/statistics & numerical data , Adult , Ethiopia/epidemiology , Female , Humans , Logistic Models , Male , Middle Aged , Odds Ratio , Pandemics/statistics & numerical data , Pregnancy , Proportional Hazards Models , Prospective Studies , SARS-CoV-2/pathogenicity , Severity of Illness Index , Time Factors , Treatment Outcome
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