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1.
Obstet Gynecol ; 138(4): 542-551, 2021 10 01.
Article in English | MEDLINE | ID: covidwho-1621687

ABSTRACT

OBJECTIVE: To examine whether the coronavirus disease 2019 (COVID-19) pandemic altered risk of adverse pregnancy-related outcomes and whether there were differences by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status among pregnant women. METHODS: In this retrospective cohort study using Epic's Cosmos research platform, women who delivered during the pandemic (March-December 2020) were compared with those who delivered prepandemic (matched months 2017-2019). Within the pandemic epoch, those who tested positive for SARS-CoV-2 infection were compared with those with negative test results or no SARS-CoV-2 diagnosis. Comparisons were performed using standardized differences, with a value greater than 0.1 indicating meaningful differences between groups. RESULTS: Among 838,489 women (225,225 who delivered during the pandemic), baseline characteristics were similar between epochs. There were no significant differences in adverse pregnancy outcomes between epochs (standardized difference<0.10). In the pandemic epoch, 108,067 (48.0%) women had SARS-CoV-2 testing available; of those, 7,432 (6.9%) had positive test results. Compared with women classified as negative for SARS-CoV-2 infection, those who tested positive for SARS-CoV-2 infection were less likely to be non-Hispanic White or Asian or to reside in the Midwest and more likely to be Hispanic, have public insurance, be obese, and reside in the South or in high social vulnerability ZIP codes. There were no significant differences in the frequency of preterm birth (8.5% vs 7.6%, standardized difference=0.032), stillbirth (0.4% vs 0.4%, standardized difference=-0.002), small for gestational age (6.4% vs 6.5%, standardized difference=-0.002), large for gestational age (7.7% vs 7.7%, standardized difference=-0.001), hypertensive disorders of pregnancy (16.3% vs 15.8%, standardized difference=0.014), placental abruption (0.5% vs 0.4%, standardized difference=0.007), cesarean birth (31.2% vs 29.4%, standardized difference=0.039), or postpartum hemorrhage (3.4% vs 3.1%, standardized difference=0.019) between those who tested positive for SARS-CoV-2 infection and those classified as testing negative. CONCLUSION: In a geographically diverse U.S. cohort, the frequency of adverse pregnancy-related outcomes did not differ between those delivering before compared with during the pandemic, nor between those classified as positive compared with negative for SARS-CoV-2 infection during pregnancy.


Subject(s)
COVID-19/epidemiology , Pregnancy Complications, Infectious/epidemiology , Pregnancy Outcome/epidemiology , Prenatal Care/statistics & numerical data , SARS-CoV-2 , Adult , COVID-19/complications , COVID-19 Testing/statistics & numerical data , Female , Humans , Infant, Newborn , Pregnancy , Pregnancy Complications, Infectious/virology , Retrospective Studies , United States/epidemiology
2.
J Prim Care Community Health ; 12: 21501319211069473, 2021.
Article in English | MEDLINE | ID: covidwho-1593650

ABSTRACT

INTRODUCTION: Federally-funded community health centers (CHCs) serve on the front lines of the COVID-19 pandemic, providing essential COVID-19 testing and care for vulnerable patient populations. Overlooked in the scholarly literature is a description of how different characteristics and vulnerabilities shaped COVID-19 care delivery at CHCs in the first year of the pandemic. Our research objective was to identify organization- and state-level factors associated with more or fewer COVID-19 care and testing visits at CHCs in 2020. METHODS: Multilevel random intercept regression models examined associations among organization and state-level predictor variables and the frequency of COVID-19 care and testing visits at CHCs in 2020. The study sample included 1267 CHCs across the 50 states and the District of Columbia. RESULTS: The average CHC provided 932 patient visits for COVID-19-related care in 2020. Yet, the CHC's role in delivering COVID-19 services proved as diverse as the populations and localities CHCs serve. For example, after adjusting for other factors, each percentage-point increase in a CHC's Hispanic patient population size was associated with a 1.3% increase in the frequency of patient visits for COVID-19 care in 2020 (P < .001). Serving a predominantly rural patient population was associated with providing significantly fewer COVID-19-related care visits (P = .002). Operating in a state that enacted a mask-wearing policy in 2020 was associated with a 26.2% lower frequency of COVID-19 testing visits at CHCs in 2020, compared to CHCs operating in states without mask-wearing policies (P = .055). CONCLUSIONS: In response to the pandemic, the federal government legislated funding to help CHCs address challenges associated with COVID-19 and provide services to medically-underserved patient populations. Policymakers will likely need to provide additional support to help CHCs address population-specific vulnerabilities affecting COVID-19 care and testing delivery, especially as highly contagious COVID-19 variants proliferate (eg, Delta and Omicron).


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19 , Community Health Centers/statistics & numerical data , COVID-19/drug therapy , Communicable Disease Control/methods , Health Policy , Humans , Masks , Pandemics , SARS-CoV-2 , United States
3.
JAMA Netw Open ; 4(12): e2140602, 2021 12 01.
Article in English | MEDLINE | ID: covidwho-1597867

ABSTRACT

Importance: During the 2020-2021 academic year, many institutions of higher education reopened to residential students while pursuing strategies to mitigate the risk of SARS-CoV-2 transmission on campus. Reopening guidance emphasized polymerase chain reaction or antigen testing for residential students and social distancing measures to reduce the frequency of close interpersonal contact, and Connecticut colleges and universities used a variety of approaches to reopen campuses to residential students. Objective: To characterize institutional reopening strategies and COVID-19 outcomes in 18 residential college and university campuses across Connecticut. Design, Setting, and Participants: This retrospective cohort study used data on COVID-19 testing and cases and social contact from 18 college and university campuses in Connecticut that had residential students during the 2020-2021 academic year. Exposures: Tests for COVID-19 performed per week per residential student. Main Outcomes and Measures: Cases per week per residential student and mean (95% CI) social contact per week per residential student. Results: Between 235 and 4603 residential students attended the fall semester across each of 18 institutions of higher education in Connecticut, with fewer residential students at most institutions during the spring semester. In census block groups containing residence halls, the fall student move-in resulted in a 475% (95% CI, 373%-606%) increase in mean contact, and the spring move-in resulted in a 561% (95% CI, 441%-713%) increase in mean contact compared with the 7 weeks prior to move-in. The association between test frequency and case rate per residential student was complex; institutions that tested students infrequently detected few cases but failed to blunt transmission, whereas institutions that tested students more frequently detected more cases and prevented further spread. In fall 2020, each additional test per student per week was associated with a decrease of 0.0014 cases per student per week (95% CI, -0.0028 to -0.00001). Conclusions and Relevance: The findings of this cohort study suggest that, in the era of available vaccinations and highly transmissible SARS-CoV-2 variants, colleges and universities should continue to test residential students and use mitigation strategies to control on-campus COVID-19 cases.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/epidemiology , COVID-19/transmission , Universities , Adolescent , COVID-19/diagnosis , Connecticut/epidemiology , Female , Housing , Humans , Male , Mass Screening/methods , Retrospective Studies , SARS-CoV-2 , Social Interaction , Young Adult
4.
Nat Microbiol ; 7(1): 97-107, 2022 01.
Article in English | MEDLINE | ID: covidwho-1596437

ABSTRACT

Global and national surveillance of SARS-CoV-2 epidemiology is mostly based on targeted schemes focused on testing individuals with symptoms. These tested groups are often unrepresentative of the wider population and exhibit test positivity rates that are biased upwards compared with the true population prevalence. Such data are routinely used to infer infection prevalence and the effective reproduction number, Rt, which affects public health policy. Here, we describe a causal framework that provides debiased fine-scale spatiotemporal estimates by combining targeted test counts with data from a randomized surveillance study in the United Kingdom called REACT. Our probabilistic model includes a bias parameter that captures the increased probability of an infected individual being tested, relative to a non-infected individual, and transforms observed test counts to debiased estimates of the true underlying local prevalence and Rt. We validated our approach on held-out REACT data over a 7-month period. Furthermore, our local estimates of Rt are indicative of 1-week- and 2-week-ahead changes in SARS-CoV-2-positive case numbers. We also observed increases in estimated local prevalence and Rt that reflect the spread of the Alpha and Delta variants. Our results illustrate how randomized surveys can augment targeted testing to improve statistical accuracy in monitoring the spread of emerging and ongoing infectious disease.


Subject(s)
COVID-19/epidemiology , Models, Statistical , SARS-CoV-2/isolation & purification , Basic Reproduction Number , Bias , COVID-19/diagnosis , COVID-19/transmission , COVID-19 Testing/statistics & numerical data , Forecasting , Humans , Prevalence , Reproducibility of Results , SARS-CoV-2/genetics , Spatio-Temporal Analysis , United Kingdom/epidemiology
5.
Proc Natl Acad Sci U S A ; 118(51)2021 12 21.
Article in English | MEDLINE | ID: covidwho-1569347

ABSTRACT

The US COVID-19 Trends and Impact Survey (CTIS) is a large, cross-sectional, internet-based survey that has operated continuously since April 6, 2020. By inviting a random sample of Facebook active users each day, CTIS collects information about COVID-19 symptoms, risks, mitigating behaviors, mental health, testing, vaccination, and other key priorities. The large scale of the survey-over 20 million responses in its first year of operation-allows tracking of trends over short timescales and allows comparisons at fine demographic and geographic detail. The survey has been repeatedly revised to respond to emerging public health priorities. In this paper, we describe the survey methods and content and give examples of CTIS results that illuminate key patterns and trends and help answer high-priority policy questions relevant to the COVID-19 epidemic and response. These results demonstrate how large online surveys can provide continuous, real-time indicators of important outcomes that are not subject to public health reporting delays and backlogs. The CTIS offers high value as a supplement to official reporting data by supplying essential information about behaviors, attitudes toward policy and preventive measures, economic impacts, and other topics not reported in public health surveillance systems.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/epidemiology , Health Status Indicators , Adult , Aged , COVID-19/diagnosis , COVID-19/prevention & control , COVID-19/transmission , COVID-19 Vaccines , Cross-Sectional Studies , Epidemiologic Methods , Female , Humans , Male , Middle Aged , Patient Acceptance of Health Care/statistics & numerical data , Social Media/statistics & numerical data , United States/epidemiology , Young Adult
6.
Comput Math Methods Med ; 2021: 9269173, 2021.
Article in English | MEDLINE | ID: covidwho-1511543

ABSTRACT

Early diagnosis of the harmful severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), along with clinical expertise, allows governments to break the transition chain and flatten the epidemic curve. Although reverse transcription-polymerase chain reaction (RT-PCR) offers quick results, chest X-ray (CXR) imaging is a more reliable method for disease classification and assessment. The rapid spread of the coronavirus disease 2019 (COVID-19) has triggered extensive research towards developing a COVID-19 detection toolkit. Recent studies have confirmed that the deep learning-based approach, such as convolutional neural networks (CNNs), provides an optimized solution for COVID-19 classification; however, they require substantial training data for learning features. Gathering this training data in a short period has been challenging during the pandemic. Therefore, this study proposes a new model of CNN and deep convolutional generative adversarial networks (DCGANs) that classify CXR images into normal, pneumonia, and COVID-19. The proposed model contains eight convolutional layers, four max-pooling layers, and two fully connected layers, which provide better results than the existing pretrained methods (AlexNet and GoogLeNet). DCGAN performs two tasks: (1) generating synthetic/fake images to overcome the challenges of an imbalanced dataset and (2) extracting deep features of all images in the dataset. In addition, it enlarges the dataset and represents the characteristics of diversity to provide a good generalization effect. In the experimental analysis, we used four distinct publicly accessible datasets of chest X-ray images (COVID-19 X-ray, COVID Chest X-ray, COVID-19 Radiography, and CoronaHack-Chest X-Ray) to train and test the proposed CNN and the existing pretrained methods. Thereafter, the proposed CNN method was trained with the four datasets based on the DCGAN synthetic images, resulting in higher accuracy (94.8%, 96.6%, 98.5%, and 98.6%) than the existing pretrained models. The overall results suggest that the proposed DCGAN-CNN approach is a promising solution for efficient COVID-19 diagnosis.


Subject(s)
Algorithms , COVID-19 Testing/methods , COVID-19/classification , COVID-19/diagnostic imaging , Deep Learning , SARS-CoV-2 , COVID-19 Testing/statistics & numerical data , Databases, Factual , Early Diagnosis , False Positive Reactions , Humans , Neural Networks, Computer , Pandemics , ROC Curve , Radiography, Thoracic/statistics & numerical data , Software Design , Tomography, X-Ray Computed/statistics & numerical data
7.
PLoS One ; 16(11): e0259538, 2021.
Article in English | MEDLINE | ID: covidwho-1502077

ABSTRACT

During the COVID-19 pandemic, West Virginia developed an aggressive SARS-CoV-2 testing strategy which included utilizing pop-up mobile testing in locations anticipated to have near-term increases in SARS-CoV-2 infections. This study describes and compares two methods for predicting near-term SARS-CoV-2 incidence in West Virginia counties. The first method, Rt Only, is solely based on producing forecasts for each county using the daily instantaneous reproductive numbers, Rt. The second method, ML+Rt, is a machine learning approach that uses a Long Short-Term Memory network to predict the near-term number of cases for each county using epidemiological statistics such as Rt, county population information, and time series trends including information on major holidays, as well as leveraging statewide COVID-19 trends across counties and county population size. Both approaches used daily county-level SARS-CoV-2 incidence data provided by the West Virginia Department Health and Human Resources beginning April 2020. The methods are compared on the accuracy of near-term SARS-CoV-2 increases predictions by county over 17 weeks from January 1, 2021- April 30, 2021. Both methods performed well (correlation between forecasted number of cases and the actual number of cases week over week is 0.872 for the ML+Rt method and 0.867 for the Rt Only method) but differ in performance at various time points. Over the 17-week assessment period, the ML+Rt method outperforms the Rt Only method in identifying larger spikes. Results show that both methods perform adequately in both rural and non-rural predictions. Finally, a detailed discussion on practical issues regarding implementing forecasting models for public health action based on Rt is provided, and the potential for further development of machine learning methods that are enhanced by Rt.


Subject(s)
COVID-19/epidemiology , Forecasting/methods , Machine Learning , COVID-19 Testing/statistics & numerical data , Humans , Incidence , Models, Statistical , Predictive Value of Tests , Rural Population , West Virginia/epidemiology
8.
PLoS One ; 16(11): e0259398, 2021.
Article in English | MEDLINE | ID: covidwho-1502074

ABSTRACT

The first case of COVID-19 in Nigeria was recorded on February 27, 2020, being an imported case by an Italian expatriate, to the country. Since then, there has been steady increase in the number of cases. However, the number of cases in Nigeria is low in comparison to cases reported by other countries with similar large populations, despite the poor health system prevailing in the country. This has been mainly attributed to the low testing capacity in Nigeria among other factors. Therefore, there is a need for innovative ways to increase the number of persons testing for COVID-19. The aim of the study was to pilot a nasopharyngeal swab self-sample collection model that would help increase COVID-19 testing while ensuring minimal person-to-person contact being experienced at the testing center. 216 participants took part in this study which was carried out at the Nigerian Institute of Medical Research between June and July 2020. Amongst the 216 participants, 174 tested negatives for both self-collected samples and samples collected by Professionals, 30 tested positive for both arms, with discrepancies occurring in 6 samples where the self-collected samples were positive while the ones collected by the professionals were negative. The same occurred in another set of 6 samples with the self-collected samples being negative and the professional-collected sample coming out positive, with a sensitivity of 83.3% and a specificity of 96.7%. The results of the interrater analysis are Kappa = 0.800 (95% CI, 0.690 to 0.910) which implies an outstanding agreement between the two COVID-19 sampling methods. Furthermore, since p< 0.001 Kappa (k) coefficient is statistically different from zero, our findings have shown that self-collected samples can be reliable in the diagnosis of COVID-19.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , COVID-19/prevention & control , Polymerase Chain Reaction/methods , Telemedicine/methods , Adolescent , Adult , Aged , COVID-19 Testing/statistics & numerical data , Diagnostic Tests, Routine , Female , Humans , Male , Middle Aged , Nigeria/epidemiology , Remote Consultation/methods , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity , Specimen Handling/methods , Young Adult
10.
MMWR Morb Mortal Wkly Rep ; 70(40): 1420-1424, 2021 Oct 08.
Article in English | MEDLINE | ID: covidwho-1456569

ABSTRACT

Most U.S. overnight youth camps did not operate during the summer of 2020 because of the COVID-19 pandemic* (1). Several that did operate demonstrated that multiple prevention strategies, including pre- and postarrival testing for SARS-CoV-2, the virus that causes COVID-19, masking, and physical distancing helped prevent the introduction and spread of COVID-19; in contrast, camps that relaxed prevention strategies, such as requiring a single prearrival test without subsequent testing, experienced outbreaks (2-4). The availability of COVID-19 vaccines for persons aged ≥12 years enabled implementation of an additional prevention strategy that was not available in summer 2020. This study assessed the number of COVID-19 cases and potential secondary spread among 7,173 staff members and campers from 50 states, 13 countries, and U.S. military overseas bases at nine independently operated U.S. summer youth camps affiliated with the same organization. The camps implemented multiple prevention strategies including vaccination, testing, podding (cohorting), masking, physical distancing, and hand hygiene during June-August 2021. Vaccination coverage was 93% among eligible persons aged ≥12 years.† All staff members (1,955) and campers (5,218) received site-specific, protocol-defined screening testing, which included prearrival testing and screening tests during the camp session (38,059 tests). Screening testing identified six confirmed COVID-19 cases (one in a staff member and five in campers) by reverse transcription-polymerase chain reaction (RT-PCR) testing (screening test positivity rate = 0.02%). Three additional cases (in two staff members and one camper) were identified based on symptoms and were confirmed by RT-PCR testing. Testing for SARS-CoV-2, isolation, and quarantine in a population with high vaccination coverage resulted in no known secondary transmission of SARS-CoV-2 identified during camp. Implementation of multicomponent strategies is critical for prevention of COVID-19 outbreaks in congregate settings, including overnight youth camps.


Subject(s)
COVID-19/prevention & control , Camping , Communicable Disease Control/methods , Disease Outbreaks/prevention & control , Adolescent , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19 Testing/statistics & numerical data , COVID-19 Vaccines/administration & dosage , Child , Female , Hand Hygiene , Humans , Male , Masks , Physical Distancing , SARS-CoV-2/isolation & purification , Seasons , United States/epidemiology , Vaccination Coverage/statistics & numerical data
11.
PLoS One ; 16(10): e0257842, 2021.
Article in English | MEDLINE | ID: covidwho-1450729

ABSTRACT

Carceral settings in the United States have been the source of many single site COVID-19 outbreaks. Quarantine is a strategy used to mitigate the spread of COVID-19 in correctional settings, and specific quarantine practices differ state to state. To better understand how states are using quarantine in prisons, we reviewed each state's definition of quarantine and compared each state's definition to the Centers for Disease Control's (CDC) definition and recommendations for quarantine in jails and prisons. Most prison systems, 45 of 53, define quarantine, but definitions vary widely. No state published definitions of quarantine that align with all CDC recommendations, and only 9 states provide quarantine data. In these states, the highest recorded quarantine rate occurred in Ohio in May 2020 at 843 per 1,000. It is necessary for prison systems to standardize their definitions of quarantine and to utilize quarantine practices in accordance with CDC recommendations. In addition, data transparency is needed to better understand the use of quarantine and its effectiveness at mitigating COVID-19 outbreaks in carceral settings.


Subject(s)
COVID-19/epidemiology , Correctional Facilities/statistics & numerical data , Quarantine/statistics & numerical data , COVID-19/diagnosis , COVID-19/virology , COVID-19 Testing/statistics & numerical data , Humans , Quarantine/standards , SARS-CoV-2/isolation & purification , United States/epidemiology
12.
PLoS Negl Trop Dis ; 15(9): e0009807, 2021 09.
Article in English | MEDLINE | ID: covidwho-1440983

ABSTRACT

BACKGROUND: Guinea reported its first case of COVID-19 on March 12, 2020. Soon thereafter, a national state of emergency was declared, all land borders were closed, schools were shut down, and public gatherings were limited. Many health activities, including field-based activities targeting neglected tropical diseases (NTDs), were paused. The World Health Organization (WHO) issued updated guidance on the resumption of NTD field-based activities on July 27, 2020. In response, the Guinea Ministry of Health (MoH) and its partners planned and resumed mass drug administration (MDA) in mid-August to September 2020 in 19 health districts. METHODOLOGY/PRINCIPAL FINDINGS: A risk-benefit assessment was conducted to identify potential risks associated with the MDA in the COVID-19 context. Following this assessment, a risk mitigation plan with barrier measures was developed to guide MDA implementation. These measures included COVID-19 testing for all national staff leaving Conakry, mask wearing, social distancing of two meters, and hand washing/sanitizing. A checklist was developed and used to monitor compliance to risk mitigation measures. Data on adherence to risk mitigation measures were collected electronically during the MDA. A total of 120 checklists, representing 120 community drug distributor (CDD) teams (two CDDs per team) and 120 households, were completed. Results indicated that washing or disinfecting hands was practiced by 68.3% of CDD teams, compared to 45.0% among households. Face masks to cover the mouth and nose were worn by 79.2% of CDD teams, while this was low among households (23.3%). In 87.5% of households, participants did not touch the dose pole and in 88.3% of CDD teams, CDDs did not touch the hands of the participants while giving the drugs. A large majority of CDD teams (94.2%) and household members (94.2%) were willing to participate in the MDA despite the pandemic. The epidemiological coverage was ≥65% for lymphatic filariasis, onchocerciasis and soil-transmitted helminths in 10 out of 19 HDs and ≥75% for schistosomiasis for school-aged children in 7 out of 11 HDs. CONCLUSIONS/SIGNIFICANCE: Guinea was one of the first countries in Africa to resume MDA activities during the COVID-19 pandemic without causing an observed increase of transmission. The development of a risk mitigation plan and a method to monitor adherence to barrier measures was critical to this unprecedented effort. The rapid incorporation of COVID-19 barrier measures and their acceptance by CDDs and household members demonstrated both the adaptability of the National NTD Program to respond to emerging issues and the commitment of the MoH to implement NTD programs.


Subject(s)
COVID-19 , Elephantiasis, Filarial/drug therapy , Mass Drug Administration , Onchocerciasis/drug therapy , Schistosomiasis/drug therapy , Antiparasitic Agents/therapeutic use , COVID-19 Testing/statistics & numerical data , Elephantiasis, Filarial/epidemiology , Elephantiasis, Filarial/prevention & control , Government Programs , Guideline Adherence , Guinea , Humans , Neglected Diseases , Onchocerciasis/epidemiology , Onchocerciasis/prevention & control , Pandemics , Risk Assessment , SARS-CoV-2 , Schistosomiasis/epidemiology , Schistosomiasis/prevention & control , Soil/parasitology
14.
J Med Virol ; 93(10): 5977-5987, 2021 10.
Article in English | MEDLINE | ID: covidwho-1432436

ABSTRACT

Accurate and comprehensive testing is crucial for practitioners to portray the pandemic. Without testing there is no data; yet, the exact number of infected people cannot be determined due to the lack of comprehensive testing. The number of seropositive for SARS-CoV-2 infection is obviously relative to the extent of testing. However, the true number of infections might be still far higher than the reported values. To compare the countries based on the number of seropositive for SARS-CoV-2 infection is misleading, as there may not be enough tests being carried out to properly monitor the outbreak. In this paper, we closely look through the COVID-19 testing results. Herein, we try to draw conclusions based on the reported data: first, the presence of a possible relationship between COVID-19 transition and patients' age will be assessed. Then, the COVID-19 case fatality rate (CFR) is compared with the age-demographic data for different countries. Based on the results, a method for estimating a lower bound (minimum) for the number of actual positive cases will be developed and validated. Results of this study have shown that CFR is a metric reflecting the spread of the virus, but is a factor of the extent of testing and does not necessarily show the real size of the outbreak. Moreover, no large difference in susceptibility by age has been found. The results suggest the similarity between the age distribution of COVID-19 and the population age-demographic is improving over the course of the pandemic. In addition, countries with lower CFRs have a more similar COVID-19 age distribution, which is a result of more comprehensive testing. Finally, a method for estimation of the real number of infected people based on the age distributions, reported CFRs, and the extent of testing will be developed and validated.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/diagnosis , COVID-19/mortality , Adolescent , Adult , Age Distribution , Aged , Aged, 80 and over , Child , Child, Preschool , Humans , Infant , Infant, Newborn , Middle Aged , Mortality , Pandemics/statistics & numerical data , SARS-CoV-2 , Young Adult
15.
Ghana Med J ; 54(4 Suppl): 97-99, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1436200

ABSTRACT

Computed Tomography (CT) scan of the chest plays an important role in the diagnosis and management of Coronavirus disease 2019 (COVID-19), the disease caused by the novel coronavirus SARS-CoV-2. COVID-19 pneumonia shows typical CT Scan features which can aid diagnoses and therefore help in the early detection and isolation of infected patients. CT scanners are readily available in many parts of Ghana. It is able to show findings typical for COVID-19 infection of the chest, even in instances where Reverse Transcription Polymerase Chain Reaction (RTPCR) misses the diagnosis. Little is known about the diagnostic potential of chest CT scan and COVID-19 among physicians even though CT scan offers a high diagnostic accuracy.


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnostic imaging , Lung/diagnostic imaging , Symptom Assessment/methods , Tomography, X-Ray Computed , Adult , Aged , COVID-19 Nucleic Acid Testing/statistics & numerical data , COVID-19 Testing/statistics & numerical data , Early Diagnosis , Female , Ghana , Humans , Lung/virology , Male , Middle Aged , Reproducibility of Results , SARS-CoV-2 , Sensitivity and Specificity
16.
Ghana Med J ; 54(4 Suppl): 52-61, 2020 Dec.
Article in English | MEDLINE | ID: covidwho-1436195

ABSTRACT

Introduction: Since the declaration of COVID-19 by the World Health Organisation (WHO) as a global pandemic on 11th March 2020, the number of deaths continue to increase worldwide. Reports on its pathologic manifestations have been published with very few from the Sub-Saharan African region. This article reports autopsies on COVID-19 patients from the Ga-East and the 37 Military Hospitals to provide pathological evidence for better understanding of COVID-19 in Ghana. Methods: Under conditions required for carrying out autopsies on bodies infected with category three infectious agents, with few modifications, complete autopsies were performed on twenty patients with ante-mortem and/or postmortem RT -PCR confirmed positive COVID-19 results, between April and June, 2020. Results: There were equal proportion of males and females. Thirteen (65%) of the patients were 55years or older with the same percentage (65%) having Type II diabetes and/or hypertension. The most significant pathological feature found at autopsy was diffuse alveolar damage. Seventy per cent (14/20) had associated thromboemboli in the lungs, kidneys and the heart. Forty per cent (6/15) of the patients that had negative results for COVID-19 by the nasopharyngeal swab test before death had positive results during postmortem using bronchopulmonary specimen. At autopsy all patients were identified to have pre-existing medical conditions. Conclusion: Diffuse alveolar damage was a key pathological feature of deaths caused by COVID-19 in all cases studied with hypertension and diabetes mellitus being major risk factors. Individuals without co-morbidities were less likely to die or suffer severe disease from SARS-CoV-2. Funding: None declared.


Subject(s)
Autopsy/statistics & numerical data , COVID-19/pathology , Hospitals, Military/statistics & numerical data , Hospitals, Municipal/statistics & numerical data , SARS-CoV-2 , COVID-19/mortality , COVID-19 Testing/methods , COVID-19 Testing/statistics & numerical data , Comorbidity , Diabetes Mellitus, Type 2/mortality , Diabetes Mellitus, Type 2/virology , Female , Ghana/epidemiology , Humans , Hypertension/mortality , Hypertension/virology , Lung/pathology , Lung/virology , Male , Middle Aged , Pulmonary Alveoli/pathology , Pulmonary Alveoli/virology , Risk Factors
17.
MMWR Morb Mortal Wkly Rep ; 70(35): 1223-1227, 2021 Sep 03.
Article in English | MEDLINE | ID: covidwho-1413074

ABSTRACT

On June 30, 2021, the Illinois Department of Public Health (IDPH) contacted CDC concerning COVID-19 outbreaks at two events sponsored by the same organization: a 5-day overnight church camp for persons aged 14-18 years and a 2-day men's conference. Neither COVID-19 vaccination nor COVID-19 testing was required before either event. As of August 13, a total of 180 confirmed and probable cases had been identified among attendees at the two events and their close contacts. Among the 122 cases associated with the camp or the conference (primary cases), 18 were in persons who were fully vaccinated, with 38 close contacts. Eight of these 38 close contacts subsequently became infected with SARS-CoV-2, the virus that causes COVID-19 (secondary cases); among the eight close contacts with secondary cases, one half (four) were fully vaccinated. Among the 180 total persons with outbreak-associated cases, five (2.8%) were hospitalized; no deaths occurred. None of the vaccinated persons with cases were hospitalized. Approximately 1,000 persons across at least four states were exposed to SARS-CoV-2 through attendance at these events or through close contact with a person who had a primary case. This investigation underscores the impact of secondary SARS-CoV-2 transmission during large events, such as camps and conferences, when COVID-19 prevention strategies are not implemented. In Los Angeles County, California, during July 2021, when the SARS-CoV-2 B.1.617.2 (Delta) variant was predominant, unvaccinated residents were five times more likely to be infected and 29 times more likely to be hospitalized from infection than were vaccinated residents (1). Implementation of multiple prevention strategies, including vaccination and nonpharmaceutical interventions such as masking, physical distancing, and screening testing, are critical to preventing SARS-CoV-2 transmission and serious complications from COVID-19.


Subject(s)
COVID-19/epidemiology , COVID-19/transmission , Camping , Congresses as Topic , Disease Outbreaks , Adolescent , Adult , Aged , COVID-19/prevention & control , COVID-19 Testing/statistics & numerical data , COVID-19 Vaccines/administration & dosage , Child , Child, Preschool , Contact Tracing , Female , Humans , Illinois/epidemiology , Male , Masks/statistics & numerical data , Middle Aged , Physical Distancing , Young Adult
18.
MMWR Morb Mortal Wkly Rep ; 70(36): 1235-1241, 2021 Sep 10.
Article in English | MEDLINE | ID: covidwho-1404132

ABSTRACT

Long-term symptoms often associated with COVID-19 (post-COVID conditions or long COVID) are an emerging public health concern that is not well understood. Prevalence of post-COVID conditions has been reported among persons who have had COVID-19 (range = 5%-80%), with differences possibly related to different study populations, case definitions, and data sources (1). Few studies of post-COVID conditions have comparisons with the general population of adults with negative test results for SARS-CoV-2, the virus that causes COVID-19, limiting ability to assess background symptom prevalence (1). CDC used a nonprobability-based Internet panel established by Porter Novelli Public Services* to administer a survey to a nationwide sample of U.S. adults aged ≥18 years to compare the prevalence of long-term symptoms (those lasting >4 weeks since onset) among persons who self-reported ever receiving a positive SARS-CoV-2 test result with the prevalence of similar symptoms among persons who reported always receiving a negative test result. The weighted prevalence of ever testing positive for SARS-CoV-2 was 22.2% (95% confidence interval [CI] = 20.6%-23.8%). Approximately two thirds of respondents who had received a positive test result experienced long-term symptoms often associated with SARS-CoV-2 infection. Compared with respondents who received a negative test result, those who received a positive test result reported a significantly higher prevalence of any long-term symptom (65.9% versus 42.9%), fatigue (22.5% versus 12.0%), change in sense of smell or taste (17.3% versus 1.7%), shortness of breath (15.5% versus 5.2%), cough (14.5% versus 4.9%), headache (13.8% versus 9.9%), and persistence (>4 weeks) of at least one initially occurring symptom (76.2% versus 69.6%). Compared with respondents who received a negative test result, a larger proportion of those who received a positive test result reported believing that receiving a COVID-19 vaccine made their long-term symptoms better (28.7% versus 15.7%). Efforts to address post-COVID conditions should include helping health care professionals recognize the most common post-COVID conditions and optimize care for patients with persisting symptoms, including messaging on potential benefits of COVID-19 vaccination.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19/complications , COVID-19/diagnosis , SARS-CoV-2/isolation & purification , Adolescent , Adult , Aged , COVID-19/epidemiology , Female , Humans , Male , Middle Aged , United States/epidemiology , Young Adult
19.
PLoS One ; 16(9): e0257112, 2021.
Article in English | MEDLINE | ID: covidwho-1398939

ABSTRACT

Public health and social interventions are critical to mitigate the spread of the coronavirus disease 2019 (COVID-19) pandemic. Ethiopia has implemented a variety of public health and social measures to control the pandemic. This study aimed to assess social distancing and public health preventive practices of government employees in response to COVID-19. A cross-sectional study was conducted among 1,573 government employees selected from 46 public institutions located in Addis Ababa. Data were collected from 8th to 19th June 2020 using a paper-based self-administered questionnaire and analyzed using SPSS version 23.0. Descriptive statistics were used to summarize the data. Binary logistic regression analyses were used to identify factors associated with outcome variables (perceived effectiveness of facemask wearing to prevent coronavirus infection, and COVID-19 testing). Majority of the participants reported facemask wearing (96%), avoiding close contact with people including handshaking (94.8%), consistently followed government recommendations (95.6%), frequent handwashing (94.5%), practiced physical distancing (89.5%), avoided mass gatherings and crowded places (88.1%), restricting movement and travelling (71.8%), and stayed home (35.6%). More than 80% of the participants perceived that consistently wearing a facemask is highly effective in preventing coronavirus infection. Respondents from Oromia perceived less about the effectiveness of wearing facemask in preventing coronavirus infection (adjusted OR = 0.27, 95% CI:0.17-0.45). About 19% of the respondents reported that they had ever tested for COVID-19. Respondents between 40-49 years old (adjusted OR = 0.41, 95% CI:0.22-0.76) and 50-66 years (adjusted OR = 0.43, 95% CI:0.19-0.95) were less likely tested for coronavirus than the younger age groups. Similarly, respondents from Oromia were less likely to test for coronavirus (adjusted OR = 0.26, 95% CI:0.12-0.56) than those from national level. Participants who were sure about the availability of COVID-19 testing were more likely to test for coronavirus. About 57% of the respondents perceived that the policy measures in response to the pandemic were inadequate. The findings showed higher social distancing and preventive practices among the government employees in response to COVID-19. Rules and regulations imposed by the government should be enforced and people should properly apply wearing facemasks, frequent handwashing, social and physical distancing measures as a comprehensive package of COVID-19 prevention and control strategies.


Subject(s)
COVID-19/prevention & control , Government Employees/statistics & numerical data , Adolescent , Adult , COVID-19 Testing/statistics & numerical data , Cross-Sectional Studies , Ethiopia , Female , Hand Disinfection/methods , Humans , Male , Masks/statistics & numerical data , Pandemics/prevention & control , Pandemics/statistics & numerical data , Physical Distancing , Surveys and Questionnaires/statistics & numerical data , Young Adult
20.
PLoS Comput Biol ; 17(9): e1009374, 2021 09.
Article in English | MEDLINE | ID: covidwho-1398922

ABSTRACT

Accurate estimates of infection prevalence and seroprevalence are essential for evaluating and informing public health responses and vaccination coverage needed to address the ongoing spread of COVID-19 in each United States (U.S.) state. However, reliable, timely data based on representative population sampling are unavailable, and reported case and test positivity rates are highly biased. A simple data-driven Bayesian semi-empirical modeling framework was developed and used to evaluate state-level prevalence and seroprevalence of COVID-19 using daily reported cases and test positivity ratios. The model was calibrated to and validated using published state-wide seroprevalence data, and further compared against two independent data-driven mathematical models. The prevalence of undiagnosed COVID-19 infections is found to be well-approximated by a geometrically weighted average of the positivity rate and the reported case rate. Our model accurately fits state-level seroprevalence data from across the U.S. Prevalence estimates of our semi-empirical model compare favorably to those from two data-driven epidemiological models. As of December 31, 2020, we estimate nation-wide a prevalence of 1.4% [Credible Interval (CrI): 1.0%-1.9%] and a seroprevalence of 13.2% [CrI: 12.3%-14.2%], with state-level prevalence ranging from 0.2% [CrI: 0.1%-0.3%] in Hawaii to 2.8% [CrI: 1.8%-4.1%] in Tennessee, and seroprevalence from 1.5% [CrI: 1.2%-2.0%] in Vermont to 23% [CrI: 20%-28%] in New York. Cumulatively, reported cases correspond to only one third of actual infections. The use of this simple and easy-to-communicate approach to estimating COVID-19 prevalence and seroprevalence will improve the ability to make public health decisions that effectively respond to the ongoing COVID-19 pandemic.


Subject(s)
COVID-19 Testing/statistics & numerical data , COVID-19 , Models, Statistical , Antibodies, Viral/blood , COVID-19/diagnosis , COVID-19/epidemiology , COVID-19/immunology , Computational Biology , Humans , Mass Screening/statistics & numerical data , Prevalence , Seroepidemiologic Studies , United States/epidemiology
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