Population-based prevalence surveys during the Covid-19 pandemic: A systematic review

Double burden of gestational diabetes and pregnancy-induced hypertension in Ethiopia: A systematic review and meta-analysis of observational studies

BACKGROUND

The coexistence of gestational diabetes mellitus (GDM) and pregnancy-induced hypertension (PIH) amplifies the risk of maternal and perinatal mortality and complications, leading to more severe adverse pregnancy outcomes. This systematic review and meta-analysis aimed to assess the double burden of GDM and PIH (GDM/PIH) among pregnant women in Ethiopia.

METHODS

A comprehensive systematic search was conducted in the databases of PubMed, Cochrane Library, Science Direct, Embase, and Google Scholar, covering studies published up to May 14, 2023. The analysis was carried out using JBI SUMARI and STATA version 17. Subgroup analyses were computed to demonstrate heterogeneity. A sensitivity analysis was performed to examine the impact of a single study on the overall estimate. Publication bias was assessed through inspection of the funnel plot and statistically using Egger's regression test.

RESULT

Of 168 retrieved studies, 15 with a total of 6391 participants were deemed eligible. The pooled prevalence of GDM/PIH co-occurrence among pregnant women in Ethiopia was 3.76% (95% CI; 3.29-4.24). No publication bias was reported, and sensitivity analysis suggested that excluded studies did not significantly alter the pooled prevalence of GDM/PIH co-occurrence. A statistically significant association between GDM and PIH was observed, with pregnant women with GDM being three times more likely to develop PIH compared to those without GDM (OR = 3.44; 95% CI; 2.15-5.53).

CONCLUSION

This systematic review and meta-analysis revealed a high dual burden of GDM and PIH among pregnant women in Ethiopia, with a significant association between the two morbidities. These findings emphasize the critical need for comprehensive antenatal care programs in Ethiopia to adequately address and monitor both GDM and PIH for improved maternal and perinatal health outcomes.

Differences in SARS-COV-2 seroprevalence in the population of Cusco, Peru

Background

The spread of the coronavirus disease 2019 (COVID-19) in Peru has been reported at the regional level, few studies have evaluated its spread at the provincial level, in which the mechanisms could be different.

Methods

We conducted an analytical, cross-sectional, multistage observational population study to assess the seroprevalence of SARS-COV-2 at the provincial and urban/rural levels in a high-altitude setting. The sampling unit was the household, including a randomly selected family member. Sampling was performed using a data collection sheet on clinical and epidemiological variables. Chemiluminescence tests were used to detect total anti-SARS-COV-2 antibodies (IgG and IgM simultaneously). The percentages were adjusted to the sampling design.

Results

The overall prevalence in the region of Cusco was 25.9%, with considerably different prevalence between the 13 provinces (from 15.9% in Acomayo to 40.1% in Canchis) and between rural (21.1%) and urban (31.7%) areas. In multivariable model, living in a rural area was a protective factor (adjusted prevalence ratio [aPR], 0.68; 95% confidence interval [CI], 0.61-0.76).

Conclusions

Geographic diversity and population density determine different prevalence rates, typically lower in rural areas, possibly due to natural social distancing or limited interaction with people at risk.

Inferring COVID-19 testing and vaccination behavior from New Jersey testing data

Characterizing the relationship between disease testing behaviors and infectious disease dynamics is of great importance for public health. Tests for both current and past infection can influence disease-related behaviors at the individual level, while population-level knowledge of an epidemic's course may feed back to affect one's likelihood of taking a test. The COVID-19 pandemic has generated testing data on an unprecedented scale for tests detecting both current infection (PCR, antigen) and past infection (serology); this opens the way to characterizing the complex relationship between testing behavior and infection dynamics. Leveraging a rich database of individualized COVID-19 testing histories in New Jersey, we analyze the behavioral relationships between PCR and serology tests, infection, and vaccination. We quantify interactions between individuals' test-taking tendencies and their past testing and infection histories, finding that PCR tests were disproportionately taken by people currently infected, and serology tests were disproportionately taken by people with past infection or vaccination. The effects of previous positive test results on testing behavior are less consistent, as individuals with past PCR positives were more likely to take subsequent PCR and serology tests at some periods of the epidemic time course and less likely at others. Lastly, we fit a model to the titer values collected from serology tests to infer vaccination trends, finding a marked decrease in vaccination rates among individuals who had previously received a positive PCR test. These results exemplify the utility of individualized testing histories in uncovering hidden behavioral variables affecting testing and vaccination.

Patient and Staff Experience of Remote Patient Monitoring-What to Measure and How: Systematic Review

BACKGROUND

Patient and staff experience is a vital factor to consider in the evaluation of remote patient monitoring (RPM) interventions. However, no comprehensive overview of available RPM patient and staff experience-measuring methods and tools exists.

OBJECTIVE

This review aimed at obtaining a comprehensive set of experience constructs and corresponding measuring instruments used in contemporary RPM research and at proposing an initial set of guidelines for improving methodological standardization in this domain.

METHODS

Full-text papers reporting on instances of patient or staff experience measuring in RPM interventions, written in English, and published after January 1, 2011, were considered for eligibility. By "RPM interventions," we referred to interventions including sensor-based patient monitoring used for clinical decision-making; papers reporting on other kinds of interventions were therefore excluded. Papers describing primary care interventions, involving participants under 18 years of age, or focusing on attitudes or technologies rather than specific interventions were also excluded. We searched 2 electronic databases, Medline (PubMed) and EMBASE, on February 12, 2021.We explored and structured the obtained corpus of data through correspondence analysis, a multivariate statistical technique.

RESULTS

In total, 158 papers were included, covering RPM interventions in a variety of domains. From these studies, we reported 546 experience-measuring instances in RPM, covering the use of 160 unique experience-measuring instruments to measure 120 unique experience constructs. We found that the research landscape has seen a sizeable growth in the past decade, that it is affected by a relative lack of focus on the experience of staff, and that the overall corpus of collected experience measures can be organized in 4 main categories (service system related, care related, usage and adherence related, and health outcome related). In the light of the collected findings, we provided a set of 6 actionable recommendations to RPM patient and staff experience evaluators, in terms of both what to measure and how to measure it. Overall, we suggested that RPM researchers and practitioners include experience measuring as part of integrated, interdisciplinary data strategies for continuous RPM evaluation.

CONCLUSIONS

At present, there is a lack of consensus and standardization in the methods used to measure patient and staff experience in RPM, leading to a critical knowledge gap in our understanding of the impact of RPM interventions. This review offers targeted support for RPM experience evaluators by providing a structured, comprehensive overview of contemporary patient and staff experience measures and a set of practical guidelines for improving research quality and standardization in this domain.

Is the surge in cesarean section rates during the COVID-19 pandemic truly substantiated?

BACKGROUND

Cesarean section (C-section) rates, deemed a critical health indicator, have experienced a historical increase. The advent of the COVID-19 pandemic significantly impacted healthcare patterns including delays or lack of follow-up in treatment and an increased number of patients with acute problems in hospitals. This study aimed to explore whether the observed surge is a genuine consequence of pandemic-related factors.

METHODS

This study employs an Interrupted Time Series (ITS) design to analyze monthly C-section rates from March 2018 to January 2023 in Kurdistan province, Iran. Segmented regression modeling is utilized for robust data analysis.

RESULTS

The C-section rate did not show a significant change immediately after the onset of COVID-19. However, the monthly trend increased significantly during the post-pandemic period (p < 0.05). Among primigravid women, a significant monthly increase was observed before February 2020 (p < 0.05). No significant change was observed in the level or trend of C-section rates among primigravid women after the onset of COVID-19.

CONCLUSION

This study underscores the significant and enduring impact of the COVID-19 pandemic in further increasing the C-section rates over the long term, the observed variations in C-section rates among primigravid women indicate that the COVID-19 pandemic had no statistically significant impact.

Correcting prevalence estimation for biased sampling with testing errors

Sampling for prevalence estimation of infection is subject to bias by both oversampling of symptomatic individuals and error-prone tests. This results in naïve estimators of prevalence (ie, proportion of observed infected individuals in the sample) that can be very far from the true proportion of infected. In this work, we present a method of prevalence estimation that reduces both the effect of bias due to testing errors and oversampling of symptomatic individuals, eliminating it altogether in some scenarios. Moreover, this procedure considers stratified errors in which tests have different error rate profiles for symptomatic and asymptomatic individuals. This results in easily implementable algorithms, for which code is provided, that produce better prevalence estimates than other methods (in terms of reducing and/or removing bias), as demonstrated by formal results, simulations, and on COVID-19 data from the Israeli Ministry of Health.

Lineage replacement and evolution captured by 3 years of the United Kingdom Coronavirus (COVID-19) Infection Survey

The Office for National Statistics Coronavirus (COVID-19) Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors, although this was also accompanied by a gradual fall in average viral burdens from June 2021 to March 2023. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non-SGTF over time. Evolution was characterized by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens.

Vitamin D status and blood group among severe COVID-19 patients

Objective

Prognosis of COVID-19 infection has been indicated to be associated with vitamin D status and ABO blood group. However, owing to discrepancies and an increased number of cases globally, the findings remain unclear. This study aimed to evaluate the association between vitamin D and ABO blood group systems in patients with severe COVID-19.

Methods

In this cross-sectional study, COVID-19 patients referred to two hospitals in the capital of Iran, Tehran, admitted to the ICU ward due to the severity of COVID-19 were evaluated. Serum vitamin D and ABO levels were evaluated in these patients. The data obtained were statistically analyzed using SPSSv24.

Results

Of 305 patients, 33.1% patients had O+ blood type, 27.8% had A+ blood type and 22.4% had B+ blood type. Vitamin D deficiency was significantly associated with a mortality rate among these patients, P<0.05. The blood group of the patients was not correlated with mortality. Thirty-seven percent of the patients in the study died because of COVID-19.

Conclusion

In our study population, mortality due to COVID-19 was significantly associated with vitamin D deficiency but not the ABO blood group. We recommend further studies in this regard that include more variable and detailed biochemical analysis.

Coronavirus Disease 2019 (COVID-19) Reinfection Rates in Malawi: A Possible Tool to Guide Vaccine Prioritisation and Immunisation Policies

As the fight against the COVID-19 pandemic continues, reports indicate that the global vaccination rate is still far below the target. Understanding the levels of reinfection may help refocus and inform policymakers on vaccination. This retrospective study in Malawi included individuals and patients who tested for COVID-19 infections via reverse transcriptase polymerase chain reaction (rt-PCR) from the data at the Public Health Institute of Malawi (PHIM). We included all data in the national line list from April 2020 to March 2022. Upon review of 47,032 records, 45,486 were included with a reported 82 (0.18) reinfection representing a rate of 0.55 (95% CI: 0.44-0.68) per 100,000 person-days of follow-up. Most reinfections occurred in the first 90 to 200 days following the initial infection, and the median time to reinfection was 175 days (IQR: 150-314), with a range of 90-563 days. The risk of reinfection was highest in the immediate 3 to 6 months following the initial infection and declined substantially after that, and age demonstrated a significant association with reinfection. Estimating the burden of SARS-CoV-2 reinfections, a specific endurance of the immunity naturally gained, and the role played by risk factors in reinfections is relevant for identifying strategies to prioritise vaccination.

Sequential adaptive strategies for sampling rare clustered populations

A new class of sampling strategies is proposed that can be applied to population-based surveys targeting a rare trait that is unevenly spread over an area of interest. Our proposal is characterised by the ability to tailor the data collection to specific features and challenges of the survey at hand. It is based on integrating an adaptive component into a sequential selection, which aims both to intensify the detection of positive cases, upon exploiting the spatial clustering, and to provide a flexible framework to manage logistics and budget constraints. A class of estimators is also proposed to account for the selection bias, that are proved unbiased for the population mean (prevalence) as well as consistent and asymptotically Normal distributed. Unbiased variance estimation is also provided. A ready-to-implement weighting system is developed for estimation purposes. Two special strategies included in the proposed class are presented, that are based on the Poisson sampling and proved more efficient. The selection of primary sampling units is also illustrated for tuberculosis prevalence surveys, which are recommended in many countries and supported by the World Health Organisation as an emblematic example of the need for an improved sampling design. Simulation results are given in the tuberculosis application to illustrate the strengths and weaknesses of the proposed sequential adaptive sampling strategies with respect to traditional cross-sectional non-informative sampling as currently suggested by World Health Organisation guidelines.

An assessment of the relationship between national rates of Covid-19 incidence and mortality as reported to an international comparison database: An ecological study

Background and Aims

Making a judgment only based on formal national reports can be misleading. We aimed to assess the relationship between countries' development indicators and reported coronavirus disease 2019 (Covid-19)-related incidences and death.

Methods

Covid-19 related incidence and death cases were extracted from the updated Humanitarian Data Exchange Website on October 8, 2021. Univariable and multivariable negative binomial regression were utilized to investigate the relationship between development indicator and incidence and mortality from Covid-19 by calculating the Incidence rate ratio (IRR), mortality rate ratio (MRR), and fatality risk ratio (FRR).

Results

Very high human development index (HDI) compared with low HDI (IRR:3.56; MRR:9.04), the proportion of physicians (IRR:1.20; MRR:1.16), besides extreme poverty (IRR:1.01; MRR:1.01) were independently correlated with the mortality and incidence rate of Covid-19. Very high HDI and population density were inversely correlated with the fatality risk (FRRs of 0.54 and 0.99). The cross-continental comparison shows Europe and the North Americas, had significantly higher incidence and mortality rates with IRR of 3.56 and 1.84 as well as MRRs of 6.65 and 3.62, respectively. Also, they inversely correlated with the fatality (FRR:0.84 and 0.91, respectively).

Conclusion

A positive correlation between the fatality rate ratio based on countries' development indicators and the reverse for the incidence and mortality rate was found. Developed countries with sensitive healthcare systems can diagnose infected cases as soon as possible. Also, the mortality rate of Covid-19 will be accurately registered and reported. Due to more access to diagnostic tests, patients are diagnosed at the initial stages and will have a better opportunity to receive treatment. This leads to higher reports of incidence/and/or mortality rates and lower fatality of COVID-19. In conclusion, more Covid-19 incidence and mortality cases in developed countries can result from a more comprehensive care system and a more accurate recording procedure.

Seroprevalence of SARS-CoV-2 and Vaccination Coverage among Residents of a Lower-Middle-Class Population in the Federal District, Brazil

Estimating seroprevalence and vaccination coverage against COVID-19 is crucial to the development of well-targeted public health policies at the local level. Here, we estimated seroprevalence and vaccination coverage in a lower-middle-class population in Brazil. We conducted an observational, cross-sectional, population-based survey from 24 September to 19 December 2021. CMIA tests were used to detect anti-SARS-CoV-2 IgG against the N-protein. The overall seroprevalence was 24.15% (177/733), and vaccination coverage was 91.40% (670/733); 72.09% (483/670) were fully vaccinated. Among vaccinated participants, seroprevalence was 24.77% (95% CI 21.50-28.04; 166/670), with a prevalence ratio (PR) of 1.03 (95% CI 0.98-1.08; p-value 0.131). Among participants who received an mRNA vaccine with S-based epitope (485), seroprevalence was 16.29% (95% CI 13.04-19.85; 79/485). Among unvaccinated participants, seroprevalence was 17.46% (95% CI 10.04-28.62; 11/63). Finally, in spite of the political climate and other possible causes for vaccine hesitancy, the positive Brazilian culture towards vaccination might have curbed hesitancy.

Seroprevalence and SARS-CoV-2 invasion in general populations: A scoping review over the first year of the pandemic

Since the beginning of the COVID-19 pandemic, counting infected people has underestimated asymptomatic cases. This literature scoping review assessed the seroprevalence progression in general populations worldwide over the first year of the pandemic. Seroprevalence studies were searched in PubMed, Web of Science and medRxiv databases up to early April 2021. Inclusion criteria were a general population of all ages or blood donors as a proxy. All articles were screened for the title and abstract by two readers, and data were extracted from selected articles. Discrepancies were resolved with a third reader. From 139 articles (including 6 reviews), the seroprevalence estimated in 41 countries ranged from 0 to 69%, with a heterogenous increase over time and continents, unevenly distributed among countries (differences up to 69%) and sometimes among regions within a country (up to 10%). The seroprevalence of asymptomatic cases ranged from 0% to 31.5%. Seropositivity risk factors included low income, low education, low smoking frequency, deprived area residency, high number of children, densely populated centres, and presence of a case in a household. This review of seroprevalence studies over the first year of the pandemic documented the progression of this virus across the world in time and space and the risk factors that influenced its spread.

Prevalence of oral manifestations in COVID-19: A systematic review

Coronavirus disease 2019 (COVID-19) is a novel disease caused by a newly identified virus Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) causing diverse systemic manifestations. The oral cavity too is not spared and the symptoms appear either independently, concurrently, or sequentially. In view of the rising documented cases of oral lesions of COVID-19, this systematic review aims to assess the prevalence of oral manifestations in COVID-19 confirmed individuals. An extensive literature search was conducted in databases like Scopus, Pubmed/Medline, Livivo, Lilacs and Google Scholar and varied oral signs and symptoms were reported as per the PRISMA guidelines. Studies published in English language literature only were included and were subjected to the risk of bias using the Joana Briggs Institute Appraisal tools for prevalence studies, case series and case reports. In a two-phase selection, 34 studies were included: 21 observational, 3 case-series and 10 case reports. These observational studies included approximately 14,003 patients from 10 countries. In this review, we explored the most commonly encountered oral and dental manifestations in COVID-19 and identified that loss of taste acuity, xerostomia and anosmia were frequently reported. Elevated incidence of opportunistic infections like mucormycosis and aspergillosis were reported during the treatment due to prolonged intake of steroids. Immunosuppression and poor oral hygiene led to secondary manifestations like enanthematous lesions. However, it is not clear that oral signs and symptoms are due to COVID-19 infection itself or are the result of extensive treatment regimen followed [PROSPERO CRD42021258264].

Limitations introduced by a low participation rate of SARS-CoV-2 seroprevalence data

BACKGROUND

There has been a large influx of COVID-19 seroprevalence studies, but comparability between the seroprevalence estimates has been an issue because of heterogeneities in testing platforms and study methodology. One potential source of heterogeneity is the response or participation rate.

METHODS

We conducted a review of participation rates (PR) in SARS-CoV-2 seroprevalence studies collected by SeroTracker and examined their effect on the validity of study conclusions. PR was calculated as the count of participants for whom the investigators had collected a valid sample, divided by the number of people invited to participate in the study. A multivariable beta generalized linear model with logit link was fitted to determine if the PR of international household and community-based seroprevalence studies was associated with the factors of interest, from 1 December 2019 to 10 March 2021.

RESULTS

We identified 90 papers based on screening and were able to calculate the PR for 35 out of 90 papers (39%), with a median PR of 70% and an interquartile range of 40.92; 61% of the studies did not report PR.

CONCLUSIONS

Many SARS-CoV-2 seroprevalence studies do not report PR. It is unclear what the median PR rate would be had a larger portion not had limitations in reporting. Low participation rates indicate limited representativeness of results. Non-probabilistic sampling frames were associated with higher participation rates but may be less representative. Standardized definitions of participation rate and data reporting necessary for the PR calculations are essential for understanding the representativeness of seroprevalence estimates in the population of interest.

[Social determinants associated with self-reporting of symptoms and access to COVID-19 testing and diagnosis in the Plurinational State of BoliviaDeterminantes sociais associados ao autorrelato de sintomas, acesso a testagem e diagnóstico de COVID-19 no Estado Plurinacional da Bolívia]

Objective

To identify the prevalence of self-reporting of symptoms and access to testing and diagnosis of coronavirus-19 disease (COVID-19), as well as its association with social determinants of health (SDH).

Methods

Cross-sectional study with a sample of 11 728 men and 12 612 women over the age of 17, based on the National Household Survey 2020. The dependent variables were the self-reporting of symptoms, access to testing, and a positive COVID-19 test. The independent variables were age, educational level, area of residence and geographic area, ethnicity, type of household, income per capita, occupation, and health insurance. Prevalences, bivariate associations, and binomial logistical regression models (odds ratio (OR), and 95% confidence interval (CI95%) were calculated.

Results

Of the total individuals included, 16% reported symptoms, 10% a test, and 4.2% a positive COVID-19 test. Inequalities were observed in the reporting of COVID-19 symptoms, with a higher probability in women whose income had fallen (OR: 1.7; CI95%: 1.2-2.4) and unemployed persons (OR: 1.2; CI95%: 1.1-1.4 for men and OR: 1.3; CI95%: 1.5-1.5 for women). In contrast, with respect to access to diagnostic tests, the highest probability was observed in people with higher education (OR: 2.4; CI95%: 1.9-2.9 for men and OR: 2.7; CI95%: 2.2-3.4 for women), whose income was maintained (OR: 1.5; CI95%: 1.3-1.9 for men and OR: 1.7; CI95%: 1.4-2.0 for women) and those in the highest quartile of per capita household income (OR: 2.0; CI95%: 1.6-2.5 for men and OR: 1.6; CI95%: 1.3-2.0 for women). The probability of reporting symptoms and getting tested, and being diagnosed with COVID-19 increased with age for people with health insurance and those living in the llanos region; however, it decreased for residents of rural areas.

Conclusions

There are inequalities in access to testing and the reporting of COVID-19 symptoms.

LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images

The syndrome called COVID-19 which was firstly spread in Wuhan, China has already been declared a globally "Pandemic." To stymie the further spread of the virus at an early stage, detection needs to be done. Artificial Intelligence-based deep learning models have gained much popularity in the detection of many diseases within the confines of biomedical sciences. In this paper, a deep neural network-based "LiteCovidNet" model is proposed that detects COVID-19 cases as the binary class (COVID-19, Normal) and the multi-class (COVID-19, Normal, Pneumonia) bifurcated based on chest X-ray images of the infected persons. An accuracy of 100% and 98.82% is achieved for binary and multi-class classification respectively which is competitive performance as compared to the other recent related studies. Hence, our methodology can be used by health professionals to validate the detection of COVID-19 infected patients at an early stage with convenient cost and better accuracy.

An analysis of 45 large-scale wastewater sites in England to estimate SARS-CoV-2 community prevalence

Accurate surveillance of the COVID-19 pandemic can be weakened by under-reporting of cases, particularly due to asymptomatic or pre-symptomatic infections, resulting in bias. Quantification of SARS-CoV-2 RNA in wastewater can be used to infer infection prevalence, but uncertainty in sensitivity and considerable variability has meant that accurate measurement remains elusive. Here, we use data from 45 sewage sites in England, covering 31% of the population, and estimate SARS-CoV-2 prevalence to within 1.1% of estimates from representative prevalence surveys (with 95% confidence). Using machine learning and phenomenological models, we show that differences between sampled sites, particularly the wastewater flow rate, influence prevalence estimation and require careful interpretation. We find that SARS-CoV-2 signals in wastewater appear 4-5 days earlier in comparison to clinical testing data but are coincident with prevalence surveys suggesting that wastewater surveillance can be a leading indicator for symptomatic viral infections. Surveillance for viruses in wastewater complements and strengthens clinical surveillance, with significant implications for public health.

[Prevalence of SARS-CoV-2 antibodies in the State of Mato Grosso, Brazil: a population-based survey]

Seroprevalence data provide relevant information on the development and progression of the COVID-19 pandemic. The study aimed to estimate the prevalence of SARS-CoV-2 antibodies in Mato Grosso State, Brazil, and its distribution according to sociodemographic and economic characteristics. This population-based serological survey was conducted in September-October 2020 in individuals 18 years or older in ten municipalities (counties) in the state of Mato Grosso. Interviews and collection of biological samples were conducted in the households, and determination of IgG antibodies to SARS-CoV-2 was performed with chemiluminescence. A total of 4,306 individuals were evaluated, and COVID-19 prevalence was estimated at 12.5% (95%CI: 10.5; 14.7), ranging from 7.4% to 24.3% between municipalities. No significant differences were found in prevalence of infection according to race/color, schooling, or family income, but lower prevalence was seen in individuals with a pensioner living in the same household, who did not receive emergency financial aid, and whose family income had not decreased after social distancing measures during the epidemic. Estimated prevalence of SARS-CoV-2 antibodies in this population-based survey is essential to measure the magnitude of the disease and will back measures to confront and control the pandemic.

Real-World Effectiveness of the mRNA COVID-19 Vaccines in Japan: A Case–Control Study

The real-world effectiveness of the coronavirus disease 2019 (COVID-19) vaccines in Japan remains unclear. This case–control study evaluated the vaccine effectiveness (VE) of two doses of mRNA vaccine, BNT162b2 or mRNA-1273, against the delta (B.1.617.2) variant in the Japanese general population in the period June–September 2021. Individuals in close contact with COVID-19 patients were tested using polymerase chain reaction (PCR). A self-administered questionnaire evaluated vaccination status, demographic data, underlying medical conditions, lifestyle, personal protective health behaviors, and living environment. Two vaccine doses were reported by 11.6% of cases (n = 389) and 35.2% of controls (n = 179). Compared with controls, cases were younger and had a lower proportion who always performed handwashing for ≥20 s, a higher proportion of alcohol consumers, and a lower proportion of individuals living in single-family homes or with commuting family members. After adjusting for these confounding factors and day of PCR testing by multivariate logistic regression analysis, the VE in the period June–July (delta variant proportion 45%) was 92% and 79% in the period August–September (delta variant proportion 89%). The adjusted VE for homestay, hotel-based isolation and quarantine, and hospitalization was 78%, 77%, and 97%, respectively. Despite declining slightly, VE against hospitalization remained robust for ~3 months after the second dose. Vaccination policymaking will require longer-term monitoring of VE against new variants.

Seroprevalence of SARS-CoV-2 in urban settings in three sub-Saharan African countries (SeroCoV): a study protocol for a household-based cross-sectional prevalence study using two-stage cluster sampling

INTRODUCTION

The current COVID-19 pandemic has impacted the entire world with increasing morbidity and mortality and has resulted in serious economic and social consequences. Assessing the burden of COVID-19 is essential for developing efficient pandemic preparedness and response strategies and for determining the impact of implemented control measures. Population-based seroprevalence surveys are critical to estimate infection rates, monitor the progression of the epidemic and to allow for the identification of persons exposed to the infection who may either have been asymptomatic or were never tested. This is especially important for countries where effective testing and tracking systems could not be established and where non-severe cases or under-reported deaths might have blurred the true burden of COVID-19. Most seroprevalence surveys performed in sub-Saharan Africa have targeted specific high risk or more easily accessible populations such as healthcare workers or blood donors, and household-based estimates are rarely available. Here, we present the study protocol for a SARS-CoV-2 seroprevalence estimation in the general population of Burkina Faso, Ghana and Madagascar in 2021.

METHODS AND ANALYSIS

The SeroCoV study is a household-based cross-sectional prevalence investigation in persons aged 10 years and older living in urban areas in six cities using a two-stage geographical cluster sampling method stratified by age and sex. The presence of anti-SARS-CoV-2 IgG antibodies will be determined using a sensitive and specific SARS-CoV-2 IgG ELISA. In addition, questionnaires will cover sociodemographic information, episodes of diseases and history of testing and treatment for COVID-like symptoms, travel history and safety measures. We will estimate the seroprevalence of SARS-CoV-2, taking into account test performance and adjusting for the age and sex of the respective populations.

ETHICS AND DISSEMINATION

Ethical approval was received for all participating countries. Results will be disseminated through reports and presentations at the country level as well as peer-reviewed publications and international scientific conferences presentations.

SARS-CoV-2 seroprevalence in a high-altitude setting in Peru: adult population-based cross-sectional study

BACKGROUND

There are several ecological studies, but few studies of the prevalence of SARS-COV-2 at high altitude. We aimed to estimate the population-based seroprevalence of SARS-COV-2 in three settings of Cusco at the end of the first wave among adults.

METHODS

A population-based survey was conducted in September 2020, in three settings in the region of Cusco: (1) Cusco city at 3,300 meters above the sea level (m.a.s.l.), (2) the periphery of Cusco (Santiago, San Jerónimo, San Sebastián, and Wanchaq) at 3,300 m.a.s.l., and (3) Quillabamba city, located at 1,050 m.a.s.l. People aged ≥ 18 years within a family unit were included. The diagnosis of SARS-CoV-2 infection was based on identifying anti- SARS-CoV-2 total antibodies (IgM and IgG) in serum using the Elecsys Anti-SARS-CoV-2 chemiluminescence test.

RESULTS

We enrolled 1924 participants from 712 families. Of the total, 637 participants were anti-SARS-CoV-2 seropositive. Seroprevalence was 38.8% (95% CI [33.4%-44.9%]) in Cusco city, 34.9% (95% CI [30.4%-40.1%]) in the periphery of Cusco, and 20.3% (95% CI [16.2%-25.6%]) in Quillabamba. In 141 families (19.8%; 95% CI [17.0%-22.8%]) the whole members were positive to the test. Living with more than three persons in the same house, a positive COVID-19 case at home, and a member who died in the last five months were factors associated with SARS-COV-2 seropositivity. Dysgeusia/dysosmia was the symptom most associated with seropositivity (aPR = 2.74, 95% CI [2.41-3.12]); whereas always wearing a face shield (aPR = 0. 73; 95% CI [0.60-0.89]) or a facial mask (aPR = 0.76, 95% CI [0.63-0. 92) reduced that probability.

CONCLUSIONS

A great proportion of Cusco's city inhabitants presented anti-SARS-CoV-2 antibodies at the end of the first wave, with significant differences between settings. Wearing masks and face shields were associated with lower rate of seropositivity; however, efforts must be made to sustain them over time since there is still a high proportion of susceptible people.

Seroprevalence of anti-SARS-CoV-2 antibodies in Africa: A systematic review and meta-analysis

We estimated the seroprevalence of anti‐severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) antibodies in residents of African countries and explored its associated factors. We searched PubMed, EMBASE, PsycINFO, AMED, CINAHL, DOAJ and Google Scholar databases for peer reviewed articles and pre‐prints that reported anti‐SARS‐CoV‐2 antibody seroprevalence of general or specific human populations resident in Africa. The eligible studies were evaluated using Joana Briggs Institute prevalence critical appraisal tool. Twenty‐three studies involving 27,735 individuals were included in our paper. The pooled seroprevalence of anti‐SARS‐CoV‐2 antibodies in Africa was 22% (95%CI: 14–31) with very high heterogeneity (I² = 100%, p < 0.001). Seroprevalence was highest in studies conducted in Central Africa compared to Southern Africa, West Africa, North Africa and East Africa respectively. The number of days between the first reported coronavirus disease 2019 case in each country and when a seroprevalence study was conducted was a significant moderator of seroprevalence. Seropositivity was numerically influenced by gender and age of the participants with males and those aged below 50 years being most affected with SARS‐CoV‐2 infection. The highest pooled seroprevalence in Africa reported in this review should be interpreted cautiously due to high heterogeneity between studies. Continued seroprevalence surveillance is warranted to establish Africa's transition towards herd immunity.

Estimating seroprevalence of SARS-CoV-2 in Ohio: A Bayesian multilevel poststratification approach with multiple diagnostic tests

Globally, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected more than 59 million people and killed more than 1.39 million. Designing and monitoring interventions to slow and stop the spread of the virus require knowledge of how many people have been and are currently infected, where they live, and how they interact. The first step is an accurate assessment of the population prevalence of past infections. There are very few population-representative prevalence studies of SARS-CoV-2 infections, and only two states in the United States-Indiana and Connecticut-have reported probability-based sample surveys that characterize statewide prevalence of SARS-CoV-2. One of the difficulties is the fact that tests to detect and characterize SARS-CoV-2 coronavirus antibodies are new, are not well characterized, and generally function poorly. During July 2020, a survey representing all adults in the state of Ohio in the United States collected serum samples and information on protective behavior related to SARS-CoV-2 and coronavirus disease 2019 (COVID-19). Several features of the survey make it difficult to estimate past prevalence: 1) a low response rate; 2) a very low number of positive cases; and 3) the fact that multiple poor-quality serological tests were used to detect SARS-CoV-2 antibodies. We describe a Bayesian approach for analyzing the biomarker data that simultaneously addresses these challenges and characterizes the potential effect of selective response. The model does not require survey sample weights; accounts for multiple imperfect antibody test results; and characterizes uncertainty related to the sample survey and the multiple imperfect, potentially correlated tests.

Estimating point prevalence of COVID-19 in Qatar's primary care registered population: an RT-PCR drive-through study protocol

BACKGROUND

The first COVID-19 cases in Qatar were reported on 29 February 2020. As the epidemic progresses, essential epidemiological information is needed to facilitate monitoring of COVID-19 in the population and plan the pandemic response in Qatar.

AIM

The primary aim of this cross-sectional study is to estimate the point prevalence of COVID-19 in Qatar's primary care registered population.

DESIGN & SETTING

A cross-sectional study design will be utilised. One publicly funded health centre from each of three geographical regions in Qatar will be identified as a study location and set up to facilitate a drive-through for the study.

METHOD

Primary Health Care Corporation (PHCC) is publicly funded and the largest primary care provider in Qatar. The study will include randomly selected individuals from the full list of PHCC's registered population on its electronic medical records system. The sample selection will be done using a proportional to size sampling technique stratified by age, sex, and nationality representative of the overall PHCC-registered population. Considering the total population registered in PHCC, a sample of 2080 is proposed. A questionnaire will be administered to collect sociodemographic information, and nasal and throat swab samples will be taken. Data will be analysed to report overall symptomatic and asymptomatic point prevalence of COVID-19.

CONCLUSION

This study, with the help of a randomly selected representative sample from Qatar's primary care registered population, will provide results that can be applied to the entire population. This study design will closely represent a real-world scenario of the outbreak and is likely to provide important data to guide COVID-19 pandemic planning and response in Qatar.