A tale of lockdown policies on the transmission of COVID-19 within and between Chinese cities: A study based on heterogeneous treatment effect.

During the early outbreak phase of COVID-19 in China, lockdowns prevailed as the only available policy tools to mitigate the spread of infection. To evaluate the impact of lockdown policies in the context of the first phase of COVID-19 pandemic, we leverage data on daily confirmed cases per million people and related characteristics of a large set of cities. The study analyzed 369 Chinese cities, among which 188 implemented lockdowns of varying severity levels from January 23 to March 31, 2020. We use nationwide Baidu Mobility data to estimate the impact of lockdown policies on mitigating COVID-19 cases through reducing human mobility. We adopt a heterogeneous treatment effect model to quantify the effect of lockdown policies on containing confirmed case counts. Our results suggest that lockdowns substantially reduced human mobility, and larger reduction in mobility occurred within-city compared to between-city. The COVID-19 daily confirmed cases per million people decreased by 9% - 9.2% for every ten-percentage point fall in within-city travel intensity in t+7 timeframe. We also find that one city's lockdowns can effectively reduce the spillover cases of the traveler's destination cities. We find no evidence that stricter lockdowns are more effective at mitigating COVID-19 risks. Our findings provide practical insights about the effectiveness of NPI during the early outbreak phase of the unprecedented pandemic.

Does the resumption of international tourism heighten COVID-19 transmission?

Reopening countries also carries the risk of another wave of infections in many parts of the world, raising the question of whether we are ready to reopen our countries. This study examines the impact of reopening countries to receive foreign tourists on the spread of COVID-19 in 2022, encompassing 83 countries worldwide. We employ spatial quantile models capable of analyzing the spatial impact of tourism on the spread of the virus at different quantile levels. The research categorizes countries into three groups: low infection rate (10th-30th quantiles), moderate infection rate (40th-60th quantiles), and high infection rate (70th-90th quantiles). This allows for a more comprehensive and detailed comparison of the impacts. Additionally, considering the spatial dimension enables the explanation of both the direct and indirect effects of tourists on the country itself and neighboring countries. The findings reveal that the number of international tourists has a significant effect on the COVID-19 infection rate, particularly in countries with high initial infection rates. However, countries that effectively controlled their infection rates at a low level could maintain a low infection rate even after reopening to foreign tourists. It is also observed that reopening a country's borders negatively impacts the infection rate of neighboring countries. These important findings imply that governments of highly infected countries should shift their focus towards bolstering their economy by promoting domestic tourism and should delay reopening until the number of infections decreases.

Study of the Vertical Transmission of COVID-19 by Using the World Health Organisation Protocol in a Tertiary Care Hospital in Eastern India.

BACKGROUND: The World Health Organisation (WHO) has established criteria to diagnose vertical transmission in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This study aimed to determine the incidence of vertical transmission of SARS-CoV-2 using WHO criteria in a tertiary care centre in eastern India. METHODS: A hospital-based prospective observational study was conducted from June 2021 to February 2022 on women admitted for delivery with a positive nasopharyngeal (NP) swab and a SARS-CoV-2 real-time reverse-transcriptase polymerase chain reaction (RT-PCR) test. Following the delivery, the amniotic fluid (AF) and swab from the placenta were tested for SARS-CoV-2 by the Truenat test. The umbilical cord and maternal blood were analyzed to detect immunoglobulin M (IgM) and immunoglobulin G (IgG). The nasopharyngeal swabs of the newborns were tested for SARS-CoV-2 by RT-PCR. RESULTS: Forty-eight SARS-CoV-2-positive asymptomatic women were included in the study. Twenty-eight (58.3%) were delivered via cesarean section. Preterm delivery occurred in 13 (27.1%) cases. In only one case, vertical transmission was confirmed as the neonate had a positive nasopharyngeal SARS-CoV-2 RT-PCR test and the cord blood was IgM positive (suggesting an immune response in the neonate). The placenta was positive in three cases, and amniotic fluid was positive in two. However, vertical transmission was deemed unlikely in these cases as there was no evidence of immune response or viral persistence according to the WHO criteria. There was one stillbirth, and it tested negative for SARS-CoV-2. CONCLUSION: This study strengthens the evidence of vertical transmission in COVID-19-positive asymptomatic mothers. The data suggest a low transmission rate.

EFFECT OF PAXLOVID TREATMENT DURING ACUTE COVID-19 ON LONG COVID ONSET: AN EHR-BASED TARGET TRIAL EMULATION FROM THE N3C AND RECOVER CONSORTIA.

Preventing and treating post-acute sequelae of SARS-CoV-2 infection (PASC), commonly known as Long COVID, has become a public health priority. In this study, we examined whether treatment with Paxlovid in the acute phase of COVID-19 helps prevent the onset of PASC. We used electronic health records from the National Covid Cohort Collaborative (N3C) to define a cohort of 426,352 patients who had COVID-19 since April 1, 2022, and were eligible for Paxlovid treatment due to risk for progression to severe COVID-19. We used the target trial emulation (TTE) framework to estimate the effect of Paxlovid treatment on PASC incidence. We estimated overall PASC incidence using a computable phenotype. We also measured the onset of novel cognitive, fatigue, and respiratory symptoms in the post-acute period. Paxlovid treatment did not have a significant effect on overall PASC incidence (relative risk [RR] = 0.98, 95% confidence interval [CI] 0.95-1.01). However, it had a protective effect on cognitive (RR = 0.90, 95% CI 0.84-0.96) and fatigue (RR = 0.95, 95% CI 0.91-0.98) symptom clusters, which suggests that the etiology of these symptoms may be more closely related to viral load than that of respiratory symptoms.

Endothelial Extracellular Vesicles Enriched in microRNA-34a Predict New-Onset Diabetes in Coronavirus Disease 2019 (COVID-19) Patients: Novel Insights for Long COVID Metabolic Sequelae.

Emerging evidence indicates that the relationship between coronavirus disease 2019 (COVID-19) and diabetes is 2-fold: 1) it is known that the presence of diabetes and other metabolic alterations poses a considerably high risk to develop a severe COVID-19; 2) patients who survived a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have an increased risk of developing new-onset diabetes. However, the mechanisms underlying this association are mostly unknown, and there are no reliable biomarkers to predict the development of new-onset diabetes. In the present study, we demonstrate that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells reliably predicts the risk of developing new-onset diabetes in COVID-19. This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. SIGNIFICANCE STATEMENT: We demonstrate for the first time that a specific microRNA (miR-34a) contained in circulating extracellular vesicles released by endothelial cells is able to reliably predict the risk of developing diabetes after having contracted coronavirus disease 2019 (COVID-19). This association was independent of age, sex, body mass index (BMI), hypertension, dyslipidemia, smoking status, and D-dimer. Our findings are also relevant when considering the emerging importance of post-acute sequelae of COVID-19, with systemic manifestations observed even months after viral negativization (long COVID).

Sliding Scale Insulin Use in Nursing Homes Before and After Onset of the COVID-19 Pandemic.

OBJECTIVE: To characterize sliding-scale insulin (SSI) use in US nursing homes (NHs) before and after the COVID-19 pandemic. DESIGN: Cross-sectional study. SETTING AND PARTICIPANTS: A total of 129,829 US NH residents on SSI (01/2018-06/2022) across 12 NH chains with a common electronic health record system. METHODS: Among all residents with at least 1 administration of SSI documented in the electronic medication administration record, we described resident demographics, frequency of SSI monotherapy vs combination therapy with another diabetes medication, number of daily capillary blood glucose readings ("fingersticks"), and hypoglycemia (capillary blood glucose <70 mg/dL) and hyperglycemia after first SSI use. We used interrupted time series analysis (ITS) with segmented linear regression models to examine whether the monthly prevalence of SSI use changed at and after the onset of the COVID-19 pandemic (March 2020). RESULTS: There were 129,829 unique NH residents with SSI use [51% women, average age 71.3 (SD 11.7) years]. Of these, 36% of residents received SSI monotherapy and 64% received SSI combination therapy. Residents on SSI received an average of 3.96 (SD 1.41) fingersticks per day. Overall, 26% of SSI users experienced a hypoglycemic event within 30 days of the first SSI dose. The ITS analysis identified a step decrease in the rate of SSI use following the onset of the COVID-19 pandemic (43 fewer SSI users per 1000 insulin users) but no change in overall trend over time from before the onset of the pandemic. CONCLUSIONS AND IMPLICATIONS: SSI use and fingerstick burden are high in NH residents. Hypoglycemia occurred commonly among residents on SSI. Future research should compare the safety and effectiveness of SSI monotherapy vs other diabetes medication regimens to guide person-centered prescribing decisions in NHs.

Assessing the impact of booster vaccination on diphtheria transmission: Mathematical modeling and risk zone mapping.

The COVID-19 pandemic caused significant disruptions in the healthcare system, affecting vaccinations and the management of diphtheria cases. As a consequence of these disruptions, numerous countries have experienced a resurgence or an increase in diphtheria cases. West Java province in Indonesia is identified as one of the high-risk areas for diphtheria, experiencing an upward trend in cases from 2021 to 2023. To analyze the situation, we developed an SIR model, which integrated DPT and booster vaccinations to determine the basic reproduction number, an essential parameter for infectious diseases. Through spatial analysis of geo-referenced data, we identified hotspots and explained diffusion in diphtheria case clusters. The calculation of R0 resulted in an R0 = 1.17, indicating the potential for a diphtheria outbreak in West Java. To control the increasing cases, one possible approach is to raise the booster vaccination coverage from the current 64.84% to 75.15%, as suggested by simulation results. Furthermore, the spatial analysis revealed that hot spot clusters were present in the western, central, and southern regions, posing a high risk not only in densely populated areas but also in rural regions. The diffusion pattern of diphtheria clusters displayed an expansion-contagious pattern. Understanding the rising trend of diphtheria cases and their geographic distribution can offer crucial insights for government and health authorities to manage the number of diphtheria cases and make informed decisions regarding the best prevention and intervention strategies.

Public holidays increased the transmission of COVID-19 in Japan, 2020-2021: a mathematical modelling study.

Objectives: Although the role of specific holidays in modifying transmission dynamics of infectious diseases has received some research attention, the epidemiological impact of public holidays on the transmission of coronavirus disease 2019 (COVID-19) remains unclear. Methods: To assess the extent of increased transmission frequency during public holidays, we collected COVID-19 incidence and mobility data in Hokkaido, Tokyo, Aichi, and Osaka from 15 February 2020 to 30 September 2021. Models linking the estimated effective reproduction number (Rt) with raw or adjusted mobility, public holidays, and the state of emergency declaration were developed. The best-fit model included public holidays as an essential input variable, and was used to calculate counterfactuals of Rt in the absence of holidays. Results: During public holidays, on average, Rt increased by 5.71%, 3.19%, 4.84%, and 24.82% in Hokkaido, Tokyo, Aichi, and Osaka, respectively, resulting in a total increase of 580 (95% confidence interval [CI], 213-954), 2,209 (95% CI, 1,230-3,201), 1,086 (95% CI, 478-1,686), and 5,211 (95% CI, 4,554-5,867) cases that were attributable to the impact of public holidays. Conclusion: Public holidays intensified the transmission of COVID-19, highlighting the importance of considering public holidays in designing appropriate public health and social measures in the future.

Quantifying the presymptomatic transmission of COVID-19 in the USA.

The emergence of many presymptomatic hidden transmission events significantly complicated the intervention and control of the spread of COVID-19 in the USA during the year 2020. To analyze the role that presymptomatic infections play in the spread of this disease, we developed a state-level metapopulation model to simulate COVID-19 transmission in the USA in 2020 during which period the number of confirmed cases was more than in any other country. We estimated that the transmission rate (i.e., the number of new infections per unit time generated by an infected individual) of presymptomatic infections was approximately 59.9% the transmission rate of reported infections. We further estimated that {at any point in time the} average proportion of infected individuals in the presymptomatic stage was consistently over 50% of all infected individuals. Presymptomatic transmission was consistently contributing over 52% to daily new infections, as well as consistently contributing over 50% to the effective reproduction number from February to December. Finally, non-pharmaceutical intervention targeting presymptomatic infections was very effective in reducing the number of reported cases. These results reveal the significant contribution that presymptomatic transmission made to COVID-19 transmission in the USA during 2020, as well as pave the way for the design of effective disease control and mitigation strategies.

Germicidal efficacy of continuous and pulsed ultraviolet-C radiation on pathogen models and SARS-CoV-2.

Ultraviolet radiation's germicidal efficacy depends on several parameters, including wavelength, radiant exposure, microbial physiology, biological matrices, and surfaces. In this work, several ultraviolet radiation sources (a low-pressure mercury lamp, a KrCl excimer, and four UV LEDs) emitting continuous or pulsed irradiation were compared. The greatest log reductions in E. coli cells and B. subtilis endospores were 4.1 ± 0.2 (18 mJ cm-2) and 4.5 ± 0.1 (42 mJ cm-2) with continuous 222 nm, respectively. The highest MS2 log reduction observed was 2.7 ± 0.1 (277 nm at 3809 mJ cm-2). Log reductions of SARS-CoV-2 with continuous 222 nm and 277 nm were ≥ 3.4 ± 0.7, with 13.3 mJ cm-2 and 60 mJ cm-2, respectively. There was no statistical difference between continuous and pulsed irradiation (0.83-16.7% [222 nm and 277 nm] or 0.83-20% [280 nm] duty rates) on E. coli inactivation. Pulsed 260 nm radiation (0.5% duty rate) at 260 nm yielded significantly greater log reduction for both bacteria than continuous 260 nm radiation. There was no statistical difference in SARS-CoV-2 inactivation between continuous and pulsed 222 nm UV-C radiation and pulsed 277 nm radiation demonstrated greater germicidal efficacy than continuous 277 nm radiation. Greater radiant exposure for all radiation sources was required to inactivate MS2 bacteriophage. Findings demonstrate that pulsed irradiation could be more useful than continuous UV radiation in human-occupied spaces, but threshold limit values should be respected. Pathogen-specific sensitivities, experimental setup, and quantification methods for determining germicidal efficacy remain important factors when optimizing ultraviolet radiation for surface decontamination or other applications.

Stability and shifts in the combined positive and negative mental health of clergy: A longitudinal latent class and latent transition analysis study of united methodist pastors before and after the onset of COVID-19.

COVID-19 and its associated restrictions presented unprecedented challenges for those in the helping professions. In this study, we seek to understand how the mental health of those who belong to one specific helping profession - clergy - changed in the context of COVID-19. Using longitudinal data of a sample of United Methodist pastors from the North Carolina Clergy Health Initiative, we conduct both cross-sectional and person-centered analyses to investigate how the overall mental health of this occupational group changed, as well as how different subgroups of clergy fared within the context of the pandemic, depending on their well-being prior to the onset of COVID-19. We found that the mental health of pastors suffered within the context of the pandemic, but that individual changes in mental health differed based on what the combined positive and negative mental health patterns of clergy were prior to the pandemic, for which we used latent class analysis to identify as Flourishing, Distressed, Languishing, or Burdened but Fulfilled. Of these subgroups, having Flourishing pre-pandemic status was protective of mental health following the onset of COVID-19, whereas the other three subgroups' mental health statuses worsened. This study is the one of the first longitudinal studies of helping professionals which has tracked changes in mental health before and after the onset of COVID-19. Our findings demonstrate the utility of considering positive and negative mental health indicators together, and they point to certain groups that can be targeted with well-being resources during future periods of acute or abnormal stress.

Mechanisms of SARS-CoV-2 Placental Transmission.

The widespread occurrence of SARS-CoV-2 infections and the diverse range of symptoms have placed significant strain on healthcare systems worldwide. Pregnancy has also been affected by COVID-19, with an increased risk of complications and unfavorable outcomes for expectant mothers. Multiple studies indicate that SARS-CoV-2 can infiltrate the placenta, breach its protective barrier, and infect the fetus. Although the precise mechanisms of intrauterine transmission remain unclear, factors such as perinatal infection, macrophages, sexual intercourse, and the virus' interaction with host angiotensin-converting enzyme 2 (ACE2) and neuropilin-1 (NRP-1) proteins appear to play a role in this process. The integrity of the placental barrier fluctuates throughout pregnancy and appears to influence the likelihood of fetal transmission. The expression of placental cell receptors, like ACE2, changes during pregnancy and in response to placental damage. However, due to the consistent presence of others, such as NRP-1, SARS-CoV-2 may potentially enter the fetus at different stages of pregnancy. NRP-1 is also found in macrophages, implicating maternal macrophages and Hofbauer cells as potential routes for viral transmission. Our current understanding of SARS-CoV-2's vertical transmission pathways remains limited. Some researchers question the ACE2-associated transmission model due to the relatively low expression of ACE2 in the placenta. Existing studies investigating perinatal transmission and the impact of sexual intercourse have either involved small sample sizes or lacked statistical significance. This review aims to explore the current state of knowledge regarding the potential mechanisms of COVID-19 vertical transmission, identifying areas where further research is needed to fill the gaps in our understanding.

Efficacy of facemasks in preventing transmission of COVID-19 in non-healthcare settings: A scoping review.

Background: During the COVID-19 pandemic, an abundance of literature relating to the efficacy of face masks on reducing transmission of COVID-19 in non-healthcare settings emerged. Aim/objective: The aim of this scoping review was to allow the identification of: types of evidence conducted in this area; knowledge gaps and common concepts relating to mask efficacy in non-healthcare settings. Methods: A comprehensive literature search was conducted in PubMed, CINAHL, MEDLINE, Embase and the Irish Management Institute bibliographic database on December 15th, 2021. All types of face masks were included. Of 722 records, 16 were included after full text screening. Findings/results: Themes from an adapted model of Howard et al. framework were used to group results and identify common concepts. The grouped thematic results were then applied to the socio-ecological model. This illustrated the multifactorial elements determining the efficacy of masks themselves while also illustrating how other factors such as individual behaviours, social interactions, settings and national policy can influence the degree of the protective effect. Discussion: The findings from this scoping review indicate that an abundance of experimental literature is available indicating that masks are effective at preventing COVID-19 transmission but their degree of efficacy is impacted by external factors. This review highlights that the quality of the evidence available is low.

Significance of weather condition, human mobility, and vaccination on global COVID-19 transmission.

The transmission growth rate of infectious diseases, particularly COVID-19, has forced governments to take immediate control decisions. Previous studies have shown that human mobility, weather condition, and vaccination are potential factors influencing virus transmission. This study investigates the contribution of weather conditions, namely temperature and precipitation, human mobility, and vaccination to coronavirus transmission. Three machine learning models: random forest (RF), XGBoost, and neural networks, are applied to predict the confirmed cases based on three aforementioned variables. All models' prediction are evaluated via spatial and temporal analysis. The spatial analysis observes the model performance over countries on certain times. The temporal analysis looks at the model prediction of each country during the specified period. The models' prediction results effectively indicate the transmission trend. The RF model performs best with a coefficient of determination of up to 89%. Meanwhile, all models confirm that vaccination is most significantly associated with COVID-19 cases.

Assessing the effects of SARS-CoV-2 vaccination on the risk of household transmission during delta variant circulation: a population-based data linkage cohort study.

Background: Data on SARS-CoV-2 vaccine effectiveness to reduce transmission of infection in household settings are limited. We examined the effects of SARS-CoV-2 vaccines on Delta variant transmission within households in an infection-naïve population. Methods: This was a population-based data linkage cohort study in the Greater Sydney Metropolitan Area, New South Wales, Australia based on cases observed in June-November 2021. In households with ≥1 confirmed COVID-19 case, we calculated adjusted odds ratios (aOR) and 95% Confidence Intervals (95% CI) for the risk of SARS-CoV-2 transmission, by vaccination status (unvaccinated, partially vaccinated, fully vaccinated, or waning) and type of vaccines (mRNA or vector-based) received by both index cases and household contacts. Findings: In 20,651 households with a single index case, 18,542 of 72,768 (25%) household contacts tested PCR-positive ≤14 days after their respective index case. Household contacts with partial, full, or waning mRNA vaccination had aORs of 0.46 (95% CI 0.40-0.52), 0.36 (95% CI 0.32-0.41) and 0.64 (95% CI 0.51-0.80) compared to unvaccinated contacts, while for vector vaccines the corresponding aORs were 0.77 (95% CI 0.67-0.89), 0.65 (95% CI 0.55-0.76), and 0.64 (95% CI 0.39-1.05). Full mRNA-vaccination in index cases compared to non-vaccination was associated with aORs between 0.09 and 0.21 depending on the vaccination status of household contacts. Interpretation: Full vaccination of household contacts reduced the odds to acquire infection with the SARS-CoV-2 Delta variant in household settings by two thirds for mRNA vaccines and by one third for vector vaccines. For index cases, being fully vaccinated with an mRNA vaccine reduced the odds of onwards transmission by four-fifths compared to unvaccinated index cases. Full vaccination offered stronger protection than partial vaccination, particularly for mRNA vaccines, but with reduced effects when the last vaccination preceded exposure by ≥3 months. Funding: New South Wales Ministry of Health.

Effectiveness of Online and Remote Interventions for Mental Health in Children, Adolescents, and Young Adults After the Onset of the COVID-19 Pandemic: Systematic Review and Meta-Analysis.

BACKGROUND: The prevalence of mental illness increased in children, adolescents, and young adults during the COVID-19 pandemic, while at the same time, access to treatment facilities has been restricted, resulting in a need for the quick implementation of remote or online interventions. OBJECTIVE: This study aimed to give an overview of randomized controlled studies examining remote or online interventions for mental health in children, adolescents, and young adults and to explore the overall effectiveness of these interventions regarding different symptoms. METHODS: A systematic literature search was conducted according to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines using PubMed, PsycInfo, Psyndex, Embase, and Google Scholar. A meta-analysis was conducted using a random effects model to calculate overall effect sizes for interventions using standardized mean differences (SMDs) for postintervention scores. RESULTS: We identified 17 articles with 8732 participants in the final sample, and 13 were included in the quantitative analysis. The studies examined different digital interventions for several outcomes, showing better outcomes than the control in some studies. Meta-analyses revealed significant medium overall effects for anxiety (SMD=0.44, 95% CI 0.20 to 0.67) and social functioning (SMD=0.42, 95% CI -0.68 to -0.17) and a large significant effect for depression (SMD=1.31, 95% CI 0.34 to 2.95). In contrast, no significant overall treatment effects for well-being, psychological distress, disordered eating, and COVID-19-related symptoms were found. CONCLUSIONS: The qualitative and quantitative analyses of the included studies show promising results regarding the effectiveness of online interventions, especially for symptoms of anxiety and depression and for training of social functioning. However, the effectiveness needs to be further investigated for other groups of symptoms in the future. All in all, more research with high-quality studies is required.

Incidence and transmission associated with respiratory viruses in an acute care facility: An observational study.

We estimated the extent of respiratory virus transmission over three pre-COVID-19 seasons. Of 16,273 assays, 22.9% (3,726) detected ≥1 respiratory virus. The frequency of putatively hospital-acquired infection ranged from 6.9% (influenza A/B) to 24.7% (adenovirus). The 176 clusters were most commonly associated with rhinovirus/enterovirus (70) and influenza A/B (62).

Estimating the Epidemic Size of Superspreading Coronavirus Outbreaks in Real Time: Quantitative Study.

BACKGROUND: Novel coronaviruses have emerged and caused major epidemics and pandemics in the past 2 decades, including SARS-CoV-1, MERS-CoV, and SARS-CoV-2, which led to the current COVID-19 pandemic. These coronaviruses are marked by their potential to produce disproportionally large transmission clusters from superspreading events (SSEs). As prompt action is crucial to contain and mitigate SSEs, real-time epidemic size estimation could characterize the transmission heterogeneity and inform timely implementation of control measures. OBJECTIVE: This study aimed to estimate the epidemic size of SSEs to inform effective surveillance and rapid mitigation responses. METHODS: We developed a statistical framework based on back-calculation to estimate the epidemic size of ongoing coronavirus SSEs. We first validated the framework in simulated scenarios with the epidemiological characteristics of SARS, MERS, and COVID-19 SSEs. As case studies, we retrospectively applied the framework to the Amoy Gardens SARS outbreak in Hong Kong in 2003, a series of nosocomial MERS outbreaks in South Korea in 2015, and 2 COVID-19 outbreaks originating from restaurants in Hong Kong in 2020. RESULTS: The accuracy and precision of the estimation of epidemic size of SSEs improved with longer observation time; larger SSE size; and more accurate prior information about the epidemiological characteristics, such as the distribution of the incubation period and the distribution of the onset-to-confirmation delay. By retrospectively applying the framework, we found that the 95% credible interval of the estimates contained the true epidemic size after 37% of cases were reported in the Amoy Garden SARS SSE in Hong Kong, 41% to 62% of cases were observed in the 3 nosocomial MERS SSEs in South Korea, and 76% to 86% of cases were confirmed in the 2 COVID-19 SSEs in Hong Kong. CONCLUSIONS: Our framework can be readily integrated into coronavirus surveillance systems to enhance situation awareness of ongoing SSEs.

The impact of changes in opioid dependency treatment upon COVID-19 transmission in Sydney, Australia: a retrospective longitudinal observational study.

BACKGROUND: In April 2020, in response to the COVID-19 public health emergency, South Eastern Sydney Local Health District (SESLHD) Drug and Alcohol services modified their delivery of opioid dependency treatment (ODT) to reduce spread of COVID-19 and maintain continuity of care by increasing use of takeaway doses (TADs), transferring clients to local community pharmacies for dosing and encouraging the use of long-acting depot buprenorphine (LADB) which enabled once a month dosing. METHODS: This study was a retrospective longitudinal case-control study conducted from August 1st, to November 30th, 2021. Eligible clients were those admitted for treatment with SESLHD ODT Services prior to August 1st,2021 and who remained in treatment beyond November 30th, 2021. COVID-19 diagnoses were determined by a COVID-19 PCR and extracted from the electronic Medical Records (eMR) Discern Reporting Portal. Demographic, clinical and dosing related data were collected from eMR and the Australian Immunisation Register (AIR). RESULTS: Clients attending SESLHD ODT services had significantly greater odds of acquiring COVID-19 than the NSW adult population at large (OR: 13.63, 95%CI: 9.64,18.88). Additionally, amongst SESLHD ODT clients, being of Aboriginal and Torres Strait Islander origin was associated with greater odds of acquiring COVID-19 (OR = 2.18, CI: 1.05,4.53); whilst being employed (OR = 0.06, CI:0.01,0.46), receiving doses at pharmacy (OR = 0.43, CI: 0.21,0.89), and being vaccinated (OR = 0.12, CI: 0.06,0.26) were associated with lower odds. Every additional day of attendance required for dosing was associated with a 5% increase in odds of acquiring COVID-19 (OR = 1.05, CI: 1.02,1.08). CONCLUSIONS: Clients attending SESLHD ODT services are significantly more likely to acquire COVID-19 than the NSW population at large. Promoting vaccination uptake, transferring clients to pharmacy, and reducing the frequency of dosing (by use of takeaway doses or long-acting depot buprenorphine) are all potential methods to reduce this risk.

Age-specific transmission dynamics of SARS-CoV-2 during the first 2 years of the pandemic.

During its first 2 years, the SARS-CoV-2 pandemic manifested as multiple waves shaped by complex interactions between variants of concern, non-pharmaceutical interventions, and the immunological landscape of the population. Understanding how the age-specific epidemiology of SARS-CoV-2 has evolved throughout the pandemic is crucial for informing policy decisions. In this article, we aimed to develop an inference-based modeling approach to reconstruct the burden of true infections and hospital admissions in children, adolescents, and adults over the seven waves of four variants (wild-type, Alpha, Delta, and Omicron BA.1) during the first 2 years of the pandemic, using the Netherlands as the motivating example. We find that reported cases are a considerable underestimate and a generally poor predictor of true infection burden, especially because case reporting differs by age. The contribution of children and adolescents to total infection and hospitalization burden increased with successive variants and was largest during the Omicron BA.1 period. However, the ratio of hospitalizations to infections decreased with each subsequent variant in all age categories. Before the Delta period, almost all infections were primary infections occurring in naive individuals. During the Delta and Omicron BA.1 periods, primary infections were common in children but relatively rare in adults who experienced either reinfections or breakthrough infections. Our approach can be used to understand age-specific epidemiology through successive waves in other countries where random community surveys uncovering true SARS-CoV-2 dynamics are absent but basic surveillance and statistics data are available.