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1.
SSRN;
Preprint in English | SSRN | ID: ppcovidwho-346217

ABSTRACT

In the early days of the COVID-19 pandemic, a multitude of mobile apps were deployed to complement manual contact tracing, quarantine and isolation efforts by central, state and local authorities in India. This was the first time that digital tools were used to augment disease surveillance efforts on a large scale. At the time of deployment and even today, these mobile apps remain experimental tools with no conclusive evidence of their effectiveness, but with known risks to privacy and data security. The public discourse examining these mobile apps has also raised several privacy and data security concerns. We add to this literature through an examination of COVID-19 mobile apps deployed by state governments and local authorities, using public health perspectives on infectious disease surveillance. We develop a framework of analysis that factors state capacity concerns, public engagement, processes and methods that facilitate continuous effectiveness evaluation, and privacy and ethical concerns. We then examine COVID-19 mobile apps against this framework of analysis. Our analysis highlights several instances of duplication due to lack of coordination amongst various stakeholders engaged in COVID-19 disease surveillance;absence of any oversight and public engagement in the development and deployment processes;mixed evidence on the integration of COVID-19 mobile apps with public health protocols, a prerequisite for conducting any effectiveness evaluation;and, weak data protection. Our findings underscore the need for a systems level approach to deploying digital disease surveillance tools, particularly the need for integrating effectiveness evaluations in the implementation process.

2.
JMIR Public Health Surveill ; 8(11): e36424, 2022 Nov 08.
Article in English | MEDLINE | ID: covidwho-2079965

ABSTRACT

BACKGROUND: The distribution of population-level real-time reverse transcription-polymerase chain reaction (RT-PCR) cycle threshold (Ct) values as a proxy of viral load may be a useful indicator for predicting COVID-19 dynamics. OBJECTIVE: The aim of this study was to determine the relationship between the daily trend of average Ct values and COVID-19 dynamics, calculated as the daily number of hospitalized patients with COVID-19, daily number of new positive tests, daily number of COVID-19 deaths, and number of hospitalized patients with COVID-19 by age. We further sought to determine the lag between these data series. METHODS: The samples included in this study were collected from March 21, 2021, to December 1, 2021. Daily Ct values of all patients who were referred to the Molecular Diagnostic Laboratory of Iran University of Medical Sciences in Tehran, Iran, for RT-PCR tests were recorded. The daily number of positive tests and the number of hospitalized patients by age group were extracted from the COVID-19 patient information registration system in Tehran province, Iran. An autoregressive integrated moving average (ARIMA) model was constructed for the time series of variables. Cross-correlation analysis was then performed to determine the best lag and correlations between the average daily Ct value and other COVID-19 dynamics-related variables. Finally, the best-selected lag of Ct identified through cross-correlation was incorporated as a covariate into the autoregressive integrated moving average with exogenous variables (ARIMAX) model to calculate the coefficients. RESULTS: Daily average Ct values showed a significant negative correlation (23-day time delay) with the daily number of newly hospitalized patients (P=.02), 30-day time delay with the daily number of new positive tests (P=.02), and daily number of COVID-19 deaths (P=.02). The daily average Ct value with a 30-day delay could impact the daily number of positive tests for COVID-19 (ß=-16.87, P<.001) and the daily number of deaths from COVID-19 (ß=-1.52, P=.03). There was a significant association between Ct lag (23 days) and the number of COVID-19 hospitalizations (ß=-24.12, P=.005). Cross-correlation analysis showed significant time delays in the average Ct values and daily hospitalized patients between 18-59 years (23-day time delay, P=.02) and in patients over 60 years old (23-day time delay, P<.001). No statistically significant relation was detected in the number of daily hospitalized patients under 5 years old (9-day time delay, P=.27) and aged 5-17 years (13-day time delay, P=.39). CONCLUSIONS: It is important for surveillance of COVID-19 to find a good indicator that can predict epidemic surges in the community. Our results suggest that the average daily Ct value with a 30-day delay can predict increases in the number of positive confirmed COVID-19 cases, which may be a useful indicator for the health system.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Middle Aged , Child, Preschool , COVID-19/epidemiology , Longitudinal Studies , Iran/epidemiology , Hospitalization
3.
Public Health Rep ; : 333549221128301, 2022 Oct 14.
Article in English | MEDLINE | ID: covidwho-2079213

ABSTRACT

More than 500 single-room occupancy hotels (SROs), a type of low-cost congregate housing with shared bathrooms and kitchens, are available in San Francisco. SRO residents include essential workers, people with disabilities, and multigenerational immigrant families. In March 2020, with increasing concerns about the potential for rapid transmission of COVID-19 among a population with disproportionate rates of comorbidity, poor access to care, and inability to self-isolate, the San Francisco Department of Public Health formed an SRO outbreak response team to identify and contain COVID-19 clusters in this congregate residential setting. Using address-matching geocoding, the team conducted active surveillance to identify new cases and outbreaks of COVID-19 at SROs. An outbreak was defined as 3 separate households in the SRO with a positive test result for COVID-19. From March 2020 through February 2021, the SRO outbreak response team conducted on-site mass testing of all residents at 52 SROs with outbreaks identified through geocoding. The rate of positive COVID-19 tests was significantly higher at SROs with outbreaks than at SROs without outbreaks (12.7% vs 6.4%; P < .001). From March through May 2020, the rate of COVID-19 cases among SRO residents was higher than among residents of other settings (ie, non-SRO residents), before decreasing and remaining at an equal level to non-SRO residents during later periods of 2020. The annual case fatality rate for SRO residents and non-SRO residents was similar (1.8% vs 1.5%). This approach identified outbreaks in a setting at high risk of COVID-19 and facilitated rapid deployment of resources. The geocoding surveillance approach could be used for other diseases and in any setting for which a list of addresses is available.

4.
Journal of Acute Disease ; 11(4):127-132, 2022.
Article in English | EMBASE | ID: covidwho-2066824

ABSTRACT

This narrative review aims to highlight some of the factors contributing to challenges faced by many countries in controlling the spread of COVID-19 pandemic that continues to rage around the world, especially after stoppage of official prevention and control activities. A literature search was conducted on PubMed, and Google using search terms 'COVID-19', 'challenges', 'prevention', and 'control' in different combinations. COVID-19 prevention and control challenges are related to health-system, vaccines, administration, and society culture. Controlling the spread of COVID-19 necessitates cooperation between community leaders, healthcare professionals, religious leaders, and the public.

5.
Am J Epidemiol ; 2022 Oct 13.
Article in English | MEDLINE | ID: covidwho-2062850

ABSTRACT

Wastewater surveillance of SARS-CoV-2 has been shown to be a valuable source of information regarding SARS-CoV-2 transmission and COVID-19 cases. Though the method has been used for several decades to track other infectious diseases, there has not been a comprehensive review outlining all of the pathogens that have been surveilled through wastewater. Herein we identify what infectious diseases have been previously studied via wastewater surveillance prior to the COVID-19 pandemic. Infectious diseases and pathogens were identified in 100 studies of wastewater surveillance across 38 countries, as well as themes of how wastewater surveillance and other measures of disease transmission were linked. Twenty-five separate pathogen families were identified in the included studies, with the majority of studies examining pathogens from the family Picornaviridae, including polio and non-polio enteroviruses. Most studies of wastewater surveillance did not link what was found in the wastewater to other measures of disease transmission. Among those studies that did, the value reported varied by study. Wastewater surveillance should be considered as a potential tool for many infectious diseases. Wastewater surveillance studies can be improved by incorporating other measures of disease transmission at the population-level including disease incidence and hospitalizations.

7.
JMIR Public Health Surveill ; 8(9): e35973, 2022 Sep 27.
Article in English | MEDLINE | ID: covidwho-2054753

ABSTRACT

BACKGROUND: Disease surveillance is a critical function of public health, provides essential information about the disease burden and the clinical and epidemiologic parameters of disease, and is an important element of effective and timely case and contact tracing. The COVID-19 pandemic demonstrates the essential role of disease surveillance in preserving public health. In theory, the standard data formats and exchange methods provided by electronic health record (EHR) meaningful use should enable rapid health care data exchange in the setting of disruptive health care events, such as a pandemic. In reality, access to data remains challenging and, even if available, often lacks conformity to regulated standards. OBJECTIVE: We sought to use regulated interoperability standards already in production to generate awareness of regional bed capacity and enhance the capture of epidemiological risk factors and clinical variables among patients tested for SARS-CoV-2. We described the technical and operational components, governance model, and timelines required to implement the public health order that mandated electronic reporting of data from EHRs among hospitals in the Chicago jurisdiction. We also evaluated the data sources, infrastructure requirements, and the completeness of data supplied to the platform and the capacity to link these sources. METHODS: Following a public health order mandating data submission by all acute care hospitals in Chicago, we developed the technical infrastructure to combine multiple data feeds from those EHR systems-a regional data hub to enhance public health surveillance. A cloud-based environment was created that received ELR, consolidated clinical data architecture, and bed capacity data feeds from sites. Data governance was planned from the project initiation to aid in consensus and principles for data use. We measured the completeness of each feed and the match rate between feeds. RESULTS: Data from 88,906 persons from CCDA records among 14 facilities and 408,741 persons from ELR records among 88 facilities were submitted. Most (n=448,380, 90.1%) records could be matched between CCDA and ELR feeds. Data fields absent from ELR feeds included travel histories, clinical symptoms, and comorbidities. Less than 5% of CCDA data fields were empty. Merging CCDA with ELR data improved race, ethnicity, comorbidity, and hospitalization information data availability. CONCLUSIONS: We described the development of a citywide public health data hub for the surveillance of SARS-CoV-2 infection. We were able to assess the completeness of existing ELR feeds, augment those feeds with CCDA documents, establish secure transfer methods for data exchange, develop a cloud-based architecture to enable secure data storage and analytics, and produce dashboards for monitoring of capacity and the disease burden. We consider this public health and clinical data registry as an informative example of the power of common standards across EHRs and a potential template for future use of standards to improve public health surveillance.


Subject(s)
COVID-19 , Health Information Exchange , COVID-19/epidemiology , Humans , Pandemics/prevention & control , Public Health , SARS-CoV-2
8.
Disease Surveillance ; 37(6):725-729, 2022.
Article in Chinese | GIM | ID: covidwho-2055481

ABSTRACT

Objective: To assess the global epidemic of Coronavirus disease 2019(COVID-19) in May 2022 and the risk of importation.

9.
Disease Surveillance ; 37(6):716-719, 2022.
Article in Chinese | CAB Abstracts | ID: covidwho-2055480

ABSTRACT

In May 2022, a total of 66 infectious diseases were reported globally, affecting 233 countries and regions. Except for influenza, the top five infectious diseases affecting greatest number of countries and regions were COVID-19 (233), monkeypox (36), dengue fever (31), measles (24) and cholera (11). The top five infectious diseases with highest case fatality rates were Ebola virus disease (100.0%), Middle East Respiratory Syndrome (34.4%), Crimean-Congo hemorrhagic fever (22.2%), Lassa fever (19.8%) and monkeypox (4.0%). The top five infectious diseases with greatest number of deaths were COVID-19, malaria, cholera, dengue fever and measles. The prevalent infectious diseases in Asia were COVID-19, dengue fever and cholera, the prevalent infectious diseases in Africa were COVID-19, Ebola virus disease, cholera, yellow fever, Lassa fever, malaria and monkeypox, the prevalent infectious diseases in America were COVID-19, dengue fever, chikungunya fever and Zika virus disease, the prevalent infectious disease in Europe were COVID-19, monkeypox and acute hepatitis of unknown aetiology.

10.
Disease Surveillance ; 37(6):802-806, 2022.
Article in Chinese | GIM | ID: covidwho-2055475

ABSTRACT

Objective: To introduce the principle and method ofa-Sutte model, establish a a-Sutte model by using software R, compare the fitting and prediction effects of thea-Sutte model and multiple seasonal autoregressive integrated moving average model, SARIMA model and provides reference for the application of thea-Sutte model in epidemic prediction.

11.
HPS Weekly Report ; 56:11, 2022.
Article in English | GIM | ID: covidwho-2044719

ABSTRACT

In recent weeks, many Ukrainian refugees have crossed into Hungary, Poland, Moldova, and Romania. The WHO works with these and other nations to increase disease surveillance and provide immunization programs according to their schedules and policies. This article provides a summary of the recommendations provided by WHO to all countries in the region. According to the guidelines, countries must continue to make efforts to ensure that their resident populations, including refugee populations, are fully vaccinated against polio, measles, rubella, COVID-19, and other vaccine-preventable diseases. Vaccination against polio, measles, and rubella must be offered as a priority to incoming refugee children under the age of six who have missed any routine vaccinations Vaccine doses must be recorded and made available to vaccinated individuals.

12.
Ann Epidemiol ; 75: 67-72, 2022 Nov.
Article in English | MEDLINE | ID: covidwho-2041516

ABSTRACT

PURPOSE: Early warning in the travel origins is crucial to prevent disease spreading. When travel origins have delays in reporting disease outbreaks, the exported cases could be used to estimate the epidemic. METHODS: We developed a Bayesian model to jointly estimate the epidemic prevalence and detection delay using the exported cases and their arrival and detection dates. We used simulation studies to discuss potential biases generated by the exported cases. We proposed a hypothesis testing framework to determine the epidemic severity. RESULTS: We applied the method to the early phase of the COVID-19 epidemic of Wuhan, United States, Italy, and Iran and found that the indicators estimated from the exported cases were consistent with the domestic data under certain scenarios. The exported cases could generate various biases if not modeled properly. We presented the required number of exported cases for determining different severity levels of the outbreak. CONCLUSIONS: The exported case data is a good addition to the domestic data but also has its drawbacks. Utilizing the diagnosis resources from all countries, we advocate that countries work collaboratively to strengthen the global infectious disease surveillance system.


Subject(s)
COVID-19 , Communicable Diseases , Epidemics , Humans , COVID-19/epidemiology , Bayes Theorem , Disease Outbreaks , Communicable Diseases/epidemiology , China/epidemiology
13.
Dental Journal ; 55(2):99-104, 2022.
Article in English | CAB Abstracts | ID: covidwho-2040549

ABSTRACT

Background: The global epidemic of COVID-19 has reached an emergency status in the health system, including dentistry. The dentist profession is inseparable from the possibility of direct or indirect contact with microorganisms in the patient's blood or saliva. National and international dental associations, such as Persatuan Dokter Gigi Indonesia and the American Dental Association, have published practice protocols that must be applied by dentists who choose to continue practicing during the COVID-19 pandemic. Dentists' knowledge of practice protocols in the current situation is very important, as it enables dentists to take infection control measures against virus transmission in the dental practice environment. Strong knowledge can have a positive impact on the psychological state of dentists, such as by reducing the anxiety level of dentists when treating patients during the pandemic. Purpose: To determine the correlation between the level of knowledge of dentists regarding practice protocols and the level of anxiety that they face regarding practicing during the COVID-19 pandemic in Indonesia.

14.
American Journal of Public Health ; 112(10):1360-1360, 2022.
Article in English | CINAHL | ID: covidwho-2039528

ABSTRACT

This section offers public health research-related news briefs as of October 1, 2022. A study evaluated the effects of the COVID-19 pandemic on drug overdose-related deaths in the U.S. and Canada. An accurate device-based method was used in a study to assess moderate to vigorous physical activity (MVPA) among adolescent girls and women in Namibia. The influenza surveillance systems in China, Malaysia, and Australia were evaluated on their adherence to World Health Organization guidance.

15.
PLoS Global Public Health ; 2(8), 2022.
Article in English | CAB Abstracts | ID: covidwho-2039236

ABSTRACT

The international tourist destination of Bali reported its first case of Coronavirus Disease 2019 or COVID-19 in March 2020. To better understand the extent of exposure of Bali's 4.3 million inhabitants to the COVID-19 virus, we performed two repeated cross-sectional serosurveys stratified by urban and rural areas. We used a highly specific multiplex assay that detects antibodies to three different viral antigens. We also assessed demographic and social risk factors and history of symptoms. Our results show that the virus was widespread in Bali by late 2020, with 16.73% (95% CI 12.22-21.12) of the population having been infected by that time. We saw no differences in seroprevalence between urban and rural areas, possibly due to extensive population mixing, and similar levels of seroprevalence by gender and among age groups, except for lower seroprevalence in the very young. We observed no difference in seroprevalence between our two closely spaced surveys. Individuals reporting symptoms in the past six months were about twice as likely to be seropositive as those not reporting symptoms. Based upon official statistics for laboratory diagnosed cases for the six months prior to the survey, we estimate that for every reported case an additional 52 cases, at least, were undetected. Our results support the hypothesis that by late 2020 the virus was widespread in Bali, but largely undetected by surveillance.

16.
PLoS Global Public Health ; 2(8), 2022.
Article in English | CAB Abstracts | ID: covidwho-2039225

ABSTRACT

Over past decades, there has been increasing geographical spread of Lassa fever (LF) cases across Nigeria and other countries in West Africa. This increase has been associated with significant morbidity and mortality despite increasing focus on the disease by both local and international scientists. Many of these studies on LF have been limited to few specialised centres in the country. This study was done to identify sociodemographic and clinical predictors of LF disease and related deaths across Nigeria. We analysed retrospective surveillance data on suspected LF cases collected during January-June 2018 and 2019. Multivariable logistic regression analyses were used to identify the factors independently associated with laboratory-confirmed LF diagnosis, and with LF-related deaths. There were confirmed 815 of 1991 suspected LF cases with complete records during this period. Of these, 724/815 confirmed cases had known clinical outcomes, of whom 100 died. LF confirmation was associated with presentation of gastrointestinal tract (aOR 3.47, 95% CI: 2.79-4.32), ear, nose and throat (aOR 2.73, 95% CI: 1.80-4.15), general systemic (aOR 2.12, 95% CI: 1.65-2.70) and chest/respiratory (aOR 1.71, 95% CI: 1.28-2.29) symptoms. Other factors were being male (aOR 1.32, 95% CI: 1.06-1.63), doing business/trading (aOR 2.16, 95% CI: 1.47-3.16) and farming (aOR 1.73, 95% CI: 1.12-2.68). Factors associated with LF mortality were a one-year increase in age (aOR 1.03, 95% CI: 1.01-1.04), bleeding (aOR 2.07, 95% CI: 1.07-4.00), and central nervous manifestations (aOR 5.02, 95% CI: 3.12-10.16). Diverse factors were associated with both LF disease and related death. A closer look at patterns of clinical variables would be helpful to support early detection and management of cases. The findings would also be useful for planning preparedness and response interventions against LF in the country and region.

17.
Healthline, Journal of Indian Association of Preventive and Social Medicine ; 13(1):83-89, 2022.
Article in English | GIM | ID: covidwho-2026834

ABSTRACT

Introduction: COVID-19 caused by SARS coronavirus two has halted life across the globe since its emergence in December 2019. Most of the infected persons are asymptomatic or have mild symptoms. Serosurvey is vital for the estimation of the burden of infection. In this context, our study objective is to estimate the Seroprevalence of SARS CoV 2 IgG among the first-year medical students after the first wave in February 2021. Method: A cross-sectional study was conducted among the first-year medical students of Veer Surendra Sai Institute of Medical Sciences and Research. All the students were enrolled, and their data & serum sample was collected. Serum samples were tested for the presence of Anti-Spike IgG. Data were analyzed by using appropriate statistical tests.

18.
Jurnal Berkala Epidemiologi / Periodic Epidemiology Journal ; 10(2):210-218, 2022.
Article in English | CAB Abstracts | ID: covidwho-2026043

ABSTRACT

Background: Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by a new type of coronavirus, and as of September 11, 2020, 210,940 cases have been reported spread across all provinces in Indonesia. Central Java is the province with the 3rd highest cumulative case as of August 24, 2020. On the other hand, Klaten District ranks 11th out of 35 Districts/Cities in Central Java, and it is classified as a moderate risk zone area. Purpose: This study aims to describe the Covid-19 cases in Klaten District.

19.
Zoonoses ; 1(5):1-7, 2021.
Article in English | CAB Abstracts | ID: covidwho-2025741

ABSTRACT

Various SARS-CoV-2 variants have continually emerged since the summer of 2020. Recently, the spread and potential effects of the Lambda variant on public health have caused great scientific and public concern. The Lambda variant (C.37), first identified in Peru in December 2020, contains a novel deletion (?246-252) and two novel mutations, L452Q and F490S, not present in the ancestral strain and other variants. The Lambda variant was designated a variant of interest in April of 2021. By the end of July, this variant sequence was detected in more than 30 countries worldwide, mostly in South America. This study analyzed the global spatiotemporal distribution of the Lambda variant from the beginning of January to the end of July from publicly available data. The Lambda variant spread rapidly in Peru and became predominant in March. Circulation of the Lambda variant has also been observed in some neighboring countries, i.e., Argentina, Chile and Ecuador, where it has remained at remarkably low levels. The circulation of the Lambda variant in other countries in South America (e.g., Brazil and Colombia) and other regions of the world has also occurred at very low levels, even though this variant has been known for a long time. Multivariate linear regression analyses of the proportion of case fatalities attributable to the Lambda variant, the new deaths and the new confirmed cases per million (7-day rolling average) in Peru did not show significant associations. A review of the most recent data on the Lambda variant has suggested this variant's relatively high infectivity in cultured cells and low neutralizing titers of convalescent sera and vaccine-elicited antibodies in vitro. However, the exact effects of this variant on clinical severity and vaccine effectiveness remain poorly documented. The currently authorized COVID-19 vaccines are still believed to provide efficient protection against the Lambda variant.

20.
JMIR Public Health Surveill ; 8(8): e37039, 2022 08 09.
Article in English | MEDLINE | ID: covidwho-2022361

ABSTRACT

BACKGROUND: Obesity is a global epidemic causing at least 2.8 million deaths per year. This complex disease is associated with significant socioeconomic burden, reduced work productivity, unemployment, and other social determinants of health (SDOH) disparities. OBJECTIVE: The objective of this study was to investigate the effects of SDOH on obesity prevalence among adults in Shelby County, Tennessee, the United States, using a geospatial machine learning approach. METHODS: Obesity prevalence was obtained from the publicly available 500 Cities database of Centers for Disease Control and Prevention, and SDOH indicators were extracted from the US census and the US Department of Agriculture. We examined the geographic distributions of obesity prevalence patterns, using Getis-Ord Gi* statistics and calibrated multiple models to study the association between SDOH and adult obesity. Unsupervised machine learning was used to conduct grouping analysis to investigate the distribution of obesity prevalence and associated SDOH indicators. RESULTS: Results depicted a high percentage of neighborhoods experiencing high adult obesity prevalence within Shelby County. In the census tract, the median household income, as well as the percentage of individuals who were Black, home renters, living below the poverty level, 55 years or older, unmarried, and uninsured, had a significant association with adult obesity prevalence. The grouping analysis revealed disparities in obesity prevalence among disadvantaged neighborhoods. CONCLUSIONS: More research is needed to examine links between geographical location, SDOH, and chronic diseases. The findings of this study, which depict a significantly higher prevalence of obesity within disadvantaged neighborhoods, and other geospatial information can be leveraged to offer valuable insights, informing health decision-making and interventions that mitigate risk factors of increasing obesity prevalence.


Subject(s)
Obesity , Residence Characteristics , Adult , Humans , Machine Learning , Obesity/epidemiology , Socioeconomic Factors , Tennessee/epidemiology , United States
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