SARS-CoV-2 infection and mortality during the first epidemic wave in Madurai, south India: a prospective, active surveillance study.
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ABSTRACT:
SUBMITTER: Laxminarayan R
PROVIDER: S-EPMC8363227 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectivesThe impact of the COVID-19 pandemic in Scotland has been amongst the most severe in Europe. Serological surveillance is critical to determine the overall extent of infection across populations and to inform the public health response. This study aimed to estimate the proportion of people who have antibodies to SARS-CoV-2 ('seroprevalence') in the general population of Scotland and to see if this changes over time.Study design/methodsBetween International Organization for Standardization (ISO) week 17 (i.e. week commencing 20th April) and ISO week 25 (week commencing 15 June), 4751 residual blood samples were obtained from regional biochemistry laboratories in six participating regional health authority areas covering approximately 75% of the Scottish population. Samples were tested for the presence of anti-SARS-CoV-2 IgG antibodies using the LIAISON®SARS-CoV-2 S1/S2 IgG assay (DiaSorin, Italy). Seroprevalence rates were adjusted for the sensitivity and specificity of the assay using Bayesian methods.ResultsThe combined adjusted seroprevalence across the study period was 4.3% (95% confidence interval: 4.2%-4.5%). The proportion varied each week between 1.9% and 6.8% with no difference in antibody positivity by age, sex or geographical area.ConclusionsAt the end of the first wave of the COVID-19 pandemic, only a small fraction of the Scottish population had antibodies to SARS-CoV-2. Control of COVID-19 requires the ability to detect asymptomatic and mild infections that would otherwise remain undetected through existing surveillance systems. This is important to determine the true number of infections within the general population which, in turn, can help to understand transmission, inform control measures and provide a denominator for the estimation of severity measures such as the proportion of infected people who have been hospitalised and/or have died.
| S-EPMC7685039 | biostudies-literature
Project description:BackgroundCOVID-19-related mortality in Belgium has drawn attention for two reasons: its high level, and a good completeness in reporting of deaths. An ad hoc surveillance was established to register COVID-19 death numbers in hospitals, long-term care facilities (LTCF) and the community. Belgium adopted broad inclusion criteria for the COVID-19 death notifications, also including possible cases, resulting in a robust correlation between COVID-19 and all-cause mortality.AimTo document and assess the COVID-19 mortality surveillance in Belgium.MethodsWe described the content and data flows of the registration and we assessed the situation as of 21 June 2020, 103 days after the first death attributable to COVID-19 in Belgium. We calculated the participation rate, the notification delay, the percentage of error detected, and the results of additional investigations.ResultsThe participation rate was 100% for hospitals and 83% for nursing homes. Of all deaths, 85% were recorded within 2 calendar days: 11% within the same day, 41% after 1 day and 33% after 2 days, with a quicker notification in hospitals than in LTCF. Corrections of detected errors reduced the death toll by 5%.ConclusionBelgium implemented a rather complete surveillance of COVID-19 mortality, on account of a rapid investment of the hospitals and LTCF. LTCF could build on past experience of previous surveys and surveillance activities. The adoption of an extended definition of 'COVID-19-related deaths' in a context of limited testing capacity has provided timely information about the severity of the epidemic.
| S-EPMC8641068 | biostudies-literature
Project description:Italy was the first European country hit by the COVID-19 pandemic and has the highest number of recorded COVID-19 deaths in Europe. This prospective cohort study of the correlates of the risk of death in COVID-19 patients was conducted at the Infectious Diseases and Intensive Care units of Luigi Sacco Hospital, Milan, Italy. The clinical characteristics of all the COVID-19 patients hospitalised in the early days of the epidemic (21 February -19 March 2020) were recorded upon admission, and the time-dependent probability of death was evaluated using the Kaplan-Meier method (censored as of 20 April 2020). Cox proportional hazard models were used to assess the factors independently associated with the risk of death. Forty-eight (20.6%) of the 233 patients followed up for a median of 40 days (interquartile range 33-47) died during the follow-up. Most were males (69.1%) and their median age was 61 years (IQR 50-72). The time-dependent probability of death was 19.7% (95% CI 14.6-24.9%) 30 days after hospital admission. Age (adjusted hazard ratio [aHR] 2.08, 95% CI 1.48-2.92 per ten years more) and obesity (aHR 3.04, 95% CI 1.42-6.49) were independently associated with an increased risk of death, which was also associated with critical disease (aHR 8.26, 95% CI 1.41-48.29), C-reactive protein levels (aHR 1.17, 95% CI 1.02-1.35 per 50?mg/L more) and creatinine kinase levels above 185 U/L (aHR 2.58, 95% CI 1.37-4.87) upon admission. Case-fatality rate of patients hospitalized with COVID-19 in the early days of the Italian epidemic was about 20%. Our study adds evidence to the notion that older age, obesity and more advanced illness are factors associated to an increased risk of death among patients hospitalized with COVID-19.
| S-EPMC7242199 | biostudies-literature
Project description:BackgroundEstimates of SARS-CoV-2 infection fatality rates (IFRs) in developing countries remain poorly characterized. Mexico has one of the highest reported COVID-19 case-fatality rates worldwide, although available estimates do not consider serologic assessment of prior exposure nor all SARS-CoV-2-related deaths. We aimed to estimate sex- and age-specific IFRs for SARS-CoV-2 in Mexico.MethodsThe total number of people in Mexico with evidence of prior SARS-CoV-2 infection was derived from National Survey of Health and Nutrition-COVID-19 (ENSANUT 2020 Covid-19)-a nationally representative serosurvey conducted from August to November 2020. COVID-19 mortality data matched to ENSANUT's dates were retrieved from the death-certificate registry, which captures the majority of COVID-19 deaths in Mexico, and from the national surveillance system, which covers the subset of COVID-19 deaths that were identified by the health system and were confirmed through a positive polymerase chain reaction test. We analysed differences in IFRs by urbanization and region.ResultsThe national SARS-CoV-2 IFR was 0.47% (95% CI 0.44, 0.50) using death certificates and 0.30% (95% CI 0.28, 0.33) using surveillance-based deaths. The IFR increased with age, being close to zero at age <30 years, but increasing to 1% at ages 50-59 years in men and 60-69 years in women, and being the highest at ≥80 years for men (5.88%) and women (6.23%). Across Mexico's nine regions, Mexico City (0.99%) had the highest and the Peninsula (0.26%) the lowest certificate-based IFRs. Metropolitan areas had higher certificate-based IFR (0.63%) than rural areas (0.17%).ConclusionAfter the first wave of the COVID-19 pandemic, the overall IFR in Mexico was comparable with those of European countries. The IFR in Mexico increased with age and was higher in men than in women. The variations in IFRs across regions and places of residence within the country suggest that structural factors related to population characteristics, pandemic containment and healthcare capabilities could have influenced lethality at the local level.
| S-EPMC8903396 | biostudies-literature
Project description:ObjectiveIn this study, we investigated the impact of COVID-19 NPIs in South Africa to understand their effectiveness in the reduction of transmission of COVID-19 in the South African population. This study also investigated the COVID-19 testing, reporting, hospitalised cases, excess deaths and COVID-19 modelling in the first wave of the COVID-19 epidemic in South Africa.MethodsA semi-reactive stochastic COVID-19 model, the ARI COVID-19 SEIR model, was used to investigate the impact of NPIs in South Africa to understand their effectiveness in the reduction of COVID-19 transmission in the South African population. COVID-19 testing, reporting, hospitalised cases and excess deaths in the first COVID-19 epidemic wave in South Africa were investigated using regressional analysis and descriptive statistics.FindingsThe general trend in population movement in South African locations shows that the COVID-19 NPIs (National Lockdown Alert Levels 5,4,3,2) were approximately 30% more effective in reducing population movement concerning each increase by 1 Alert Level. The translated reduction in the effective SARS-CoV-2 daily contact number (β) was 6.12% to 36.1% concerning increasing Alert Levels. Due to the implemented NPIs, the effective SARS-CoV-2 daily contact number in the first COVID-19 epidemic wave in South Africa was reduced by 58.1-71.1% while the peak was delayed by 84 days. The estimated COVID-19 reproductive number was between 1.98 to 0.40. During South Africa's first COVID-19 epidemic wave, the mean COVID-19 admission status in South African hospitals was 58.5%, 95% CI [58.1-59.0] in the general ward, 13.4%, 95% CI [13.1-13.7] in the intensive care unit, 13.3%, 95% CI [12.6-14.0] on oxygen, 6.37%, 95% CI [6.23-6.51] in high care, 6.29%, 95% CI [6.02-6.55] on ventilator and 2.13%, 95% CI [1.87-2.43] in isolation ward respectively. The estimated mean South African COVID-19 patient discharge rate was 11.9 days per patient. While the estimated mean of the South African COVID-19 patient case fatality rate (CFR) in hospital and outside the hospital was 2.06%, 95% CI [1.86-2.25] (deaths per admitted patients) and 2.30%, 95% CI [1.12-3.83](deaths per severe and critical cases) respectively. The relatively high coefficient of variance in COVID-19 model outputs observed in this study shows the uncertainty in the accuracy of the reviewed COVID-19 models in predicting the severity of COVID-19. However, the reviewed COVID-19 models were accurate in predicting the progression of the first COVID-19 epidemic wave in South Africa.ConclusionThe results from this study show that the COVID-19 NPI policies implemented by the Government of South Africa played a significant role in the reduction of COVID-19 active, hospitalised cases and deaths in South Africa's first COVID-19 epidemic wave. The results also show the use of COVID-19 modelling to understand the COVID-19 pandemic and the impact of regressor variables in an epidemic.
| S-EPMC10403893 | biostudies-literature
Project description:Surveillance of SARS-CoV-2 and organic tracers (OTs) were conducted in the community wastewater of Chennai city and the suburbs, South India, during partial and post lockdown phases (August-September 2020) as a response to the coronavirus disease 2019 (COVID-19) pandemic. Wastewater samples were collected from four sewage treatment plants (STPs), five sewage pumping stations (SPSs) and at different time intervals from a suburban hospital wastewater (HWW). Four different methods of wastewater concentrations viz., composite (COM), supernatant (SUP), sediment (SED), and syringe filtration (SYR) were subjected to quantitative real time-polymerase chain reaction (qRT-PCR). Unlike HWW, STP inlet, sludge and SPS samples were found with higher loading of SARS-CoV-2 by SED followed by SUP method. Given the higher levels of dissolved and suspended solids in STPs and SPSs over HWW, we suspect that this enveloped virus might exhibit the tendency of higher partitioning in solid phase. Cycle threshold (Ct) values were < 30 in 50% of the HWW samples indicating higher viral load from the COVID-19 infected patients. In the STP outlets, a strict decline of biochemical oxygen demand, >95% removal of caffeine, and absence of viral copies reflect the efficiency of the treatment plants in Chennai city. Among the detected OTs, a combination of maximum dynamic range and high concurrence percentage was observed for caffeine and N1 gene of SARS-CoV-2. Hence, we suggest that caffeine can be used as an indicator for the removal of SARS-CoV-2 by STPs. Our predicted estimated number of cases are in line with the available clinical data from the catchments. Densely distributed population of the Koyambedu catchment could be partly responsible for the high proportion of estimated infected individuals during the study period.
| S-EPMC7936810 | biostudies-literature
Project description:ObjectivesTo estimate SARS-CoV-2-specific antibody seroprevalence after the first epidemic wave of coronavirus disease 2019 (COVID-19) in Sydney.Setting, participantsPeople of any age who had provided blood for testing at selected diagnostic pathology services (general pathology); pregnant women aged 20-39 years who had received routine antenatal screening; and Australian Red Cross Lifeblood plasmapheresis donors aged 20-69 years.DesignCross-sectional study; testing of de-identified residual blood specimens collected during 20 April - 2 June 2020.Main outcome measureEstimated proportions of people seropositive for anti-SARS-CoV-2-specific IgG, adjusted for test sensitivity and specificity.ResultsThirty-eight of 5339 specimens were IgG-positive (general pathology, 19 of 3231; antenatal screening, 7 of 560; plasmapheresis donors, 12 of 1548); there were no clear patterns by age group, sex, or location of residence. Adjusted estimated seroprevalence among people who had had general pathology blood tests (all ages) was 0.15% (95% credible interval [CrI], 0.04-0.41%), and 0.29% (95% CrI, 0.04-0.75%) for plasmapheresis donors (20-69 years). Among 20-39-year-old people, the age group common to all three collection groups, adjusted estimated seroprevalence was 0.24% (95% CrI, 0.04-0.80%) for the general pathology group, 0.79% (95% CrI, 0.04-1.88%) for the antenatal screening group, and 0.69% (95% CrI, 0.04-1.59%) for plasmapheresis donors.ConclusionsEstimated SARS-CoV-2 seroprevalence was below 1%, indicating that community transmission was low during the first COVID-19 epidemic wave in Sydney. These findings suggest that early control of the spread of COVID-19 was successful, but efforts to reduce further transmission remain important.
| S-EPMC8014239 | biostudies-literature
Project description:During the first phase of the COVID-19 epidemic, New York City rapidly became the epicenter of the pandemic in the United States. While molecular phylogenetic analyses have previously highlighted multiple introductions and a period of cryptic community transmission within New York City, little is known about the circulation of SARS-CoV-2 within and among its boroughs. We here perform phylogeographic investigations to gain insights into the circulation of viral lineages during the first months of the New York City outbreak. Our analyses describe the dispersal dynamics of viral lineages at the state and city levels, illustrating that peripheral samples likely correspond to distinct dispersal events originating from the main metropolitan city areas. In line with the high prevalence recorded in this area, our results highlight the relatively important role of the borough of Queens as a transmission hub associated with higher local circulation and dispersal of viral lineages toward the surrounding boroughs.
| S-EPMC8136714 | biostudies-literature
Project description:In temperate countries, death rates increase in winter, but influenza epidemics often cause greater increases. The death rate time series that occurs without epidemic influenza can be called a seasonal baseline. Differentiating observed death rates from the seasonally oscillating baseline provides estimated influenza-associated death rates. During 2003-2009 in New South Wales, Australia, we used a Serfling approach with robust regression to estimate age-specific weekly baseline all-cause death rates. Total differences between weekly observed and baseline rates during May-September provided annual estimates of influenza-associated death rates. In 2009, which included our first wave of pandemic (H1N1) 2009, the all-age death rate was 6.0 (95% confidence interval 3.1-8.9) per 100,000 persons lower than baseline. In persons ?80 years of age, it was 131.6 (95% confidence interval 126.2-137.1) per 100,000 lower. This estimate is consistent with a pandemic virus causing mild illness in most persons infected and sparing older persons.
| S-EPMC3294965 | biostudies-literature
Project description:BackgroundThe first wave of the COVID-19 pandemic in France was associated with high excess mortality, and anecdotal evidence pointed to differing excess mortality patterns depending on social and environmental determinants. In this study we aimed to investigate the spatial distribution of excess mortality during the first wave of the COVID-19 pandemic in France and relate it at the subnational level to contextual determinants from various dimensions (socioeconomic, population density, overall health status, healthcare access etc.). We also explored whether the determinants identified at the national level varied depending on geographical location.MethodsWe used available national data on deaths in France to calculate excess mortality by department for three age groups: 0-49, 50-74 and > 74 yrs. between March 1st and April 27th, 2020. We selected 15 variables at the department level that represent four dimensions that may be related to overall mortality at the ecological level, two representing population-level vulnerabilities (morbidity, social deprivation) and two representing environmental-level vulnerabilities (primary healthcare supply, urbanization). We modelled excess mortality by age group for our contextual variables at the department level. We conducted both a global (i.e., country-wide) analysis and a multiscale geographically weighted regression (MGWR) model to account for the spatial variations in excess mortality.ResultsIn both age groups, excess all-cause mortality was significantly higher in departments where urbanization was higher (50-74 yrs.: β = 15.33, p < 0.001; > 74 yrs.: β = 18.24, p < 0.001) and the supply of primary healthcare providers lower (50-74 yrs.: β = - 8.10, p < 0.001; > 74 yrs.: β = - 8.27, p < 0.001). In the 50-74 yrs. age group, excess mortality was negatively associated with the supply of pharmacists (β = - 3.70, p < 0.02) and positively associated with work-related mobility (β = 4.62, p < 0.003); in the > 74 yrs. age group our measures of deprivation (β = 15.46, p < 0.05) and morbidity (β = 0.79, p < 0.008) were associated with excess mortality. Associations between excess mortality and contextual variables varied significantly across departments for both age groups.ConclusionsPublic health strategies aiming at mitigating the effects of future epidemics should consider all dimensions involved to develop efficient and locally tailored policies within the context of an evolving, socially and spatially complex situation.
| S-EPMC8611998 | biostudies-literature