A Spatiotemporal Solution to Control COVID-19 Transmission at the Community Scale for Returning to Normalcy: COVID-19 Symptom Onset Risk Spatiotemporal Analysis.

BACKGROUND: Following the recent COVID-19 pandemic, returning to normalcy has become the primary goal of global cities. The key for returning to normalcy is to avoid affecting social and economic activities while supporting precise epidemic control. Estimation models for the spatiotemporal spread of the epidemic at the refined scale of cities that support precise epidemic control are limited. For most of 2021, Hong Kong has remained at the top of the "global normalcy index" because of its effective responses. The urban-community-scale spatiotemporal onset risk prediction model of COVID-19 symptom has been used to assist in the precise epidemic control of Hong Kong. OBJECTIVE: Based on the spatiotemporal prediction models of COVID-19 symptom onset risk, the aim of this study was to develop a spatiotemporal solution to assist in precise prevention and control for returning to normalcy. METHODS: Over the years 2020 and 2021, a spatiotemporal solution was proposed and applied to support the epidemic control in Hong Kong. An enhanced urban-community-scale geographic model was proposed to predict the risk of COVID-19 symptom onset by quantifying the impact of the transmission of SARS-CoV-2 variants, vaccination, and the imported case risk. The generated prediction results could be then applied to establish the onset risk predictions over the following days, the identification of high-onset-risk communities, the effectiveness analysis of response measures implemented, and the effectiveness simulation of upcoming response measures. The applications could be integrated into a web-based platform to assist the antiepidemic work. RESULTS: Daily predicted onset risk in 291 tertiary planning units (TPUs) of Hong Kong from January 18, 2020, to April 22, 2021, was obtained from the enhanced prediction model. The prediction accuracy in the following 7 days was over 80%. The prediction results were used to effectively assist the epidemic control of Hong Kong in the following application examples: identified communities within high-onset-risk always only accounted for 2%-25% in multiple epidemiological scenarios; effective COVID-19 response measures, such as prohibiting public gatherings of more than 4 people were found to reduce the onset risk by 16%-46%; through the effect simulation of the new compulsory testing measure, the onset risk was found to be reduced by more than 80% in 42 (14.43%) TPUs and by more than 60% in 96 (32.99%) TPUs. CONCLUSIONS: In summary, this solution can support sustainable and targeted pandemic responses for returning to normalcy. Faced with the situation that may coexist with SARS-CoV-2, this study can not only assist global cities in responding to the future epidemics effectively but also help to restore social and economic activities and people's normal lives.

How to control the spatiotemporal spread of Omicron in the region with low vaccination rates.

Currently, finding ways to effectively control the spread of Omicron in regions with low vaccination rates is an urgent issue. In this study, we use a district-level model for predicting the COVID-19 symptom onset risk to explore and control the whole process of spread of Omicron in South Africa at a finer spatial scale. We found that in the early stage of the accelerated spread, Omicron spreads rapidly from the districts at the center of human mobility to other important districts of the human mobility network and its peripheral districts. In the subsequent diffusion-contraction stage, Omicron rapidly spreads to districts with low human mobility and then mainly contracts to districts with the highest human mobility. We found that increasing daily vaccination rates 10 times mainly reduced the symptom onset risk in remote areas with low human mobility. Implementing Alert Level 5 in the three districts at the epicenter, and Alert Level 1 in the remaining 49 districts, the spatial spread related to human mobility was effectively restricted, and the daily onset risk in districts with high human mobility also decreased by 20-80%.

Transient expression of antinuclear RNP-A antibodies in patients with acute COVID-19 infection.

Introduction: Viral infections have been implicated in the initiation of the autoimmune diseases. Recent reports suggest that a proportion of patients with COVID-19 develop severe disease with multiple organ injuries. We evaluated the relationship between COVID-19 severity, prevalence and persistence of antinuclear and other systemic and organ specific autoantibodies as well as SARS-CoV-2 infection specific anti-nucleocapsid (N) IgG antibodies and protective neutralizing antibody (Nab) levels. Methods: Samples from 119 COVID-19 patients categorized based on their level of care and 284 healthy subjects were tested for the presence and persistence of antinuclear and other systemic and organ specific autoantibodies as well as SARS-CoV-2 and neutralizing antibody levels. Results: The data shows significantly increased levels of anti RNP-A, anti-nucleocapsid and neutralizing antibody among patients receiving ICU care compared to non-ICU care. Furthermore, subjects receiving ICU care demonstrated significantly higher nucleocapsid IgG levels among the RNP-A positive cohort compared to RNP-A negative cohort. Notably, the expression of anti RNP-A antibodies is transient that reverts to non-reactive status between 20 and 60 days post symptom onset. Conclusions: COVID-19 patients in ICU care exhibit significantly higher levels of transient RNP-A autoantibodies, anti-nucleocapsid, and SARS-CoV-2 neutralizing antibodies compared to patients in non-ICU care.

Two-Dose Vaccination Significantly Prolongs the Duration from Symptom Onset to Death: A Retrospective Study Based on 173,894 SARS-CoV-2 Cases in Khyber Pakhtunkhwa, Pakistan.

This research was carried out to quantify the duration from symptom onset to recovery/death (SOR/SOD) during the first four waves and the Alpha/Delta period of the epidemic in Khyber Pakhtunkhwa, Pakistan, and identify the associated factors. A total of 173,894 COVID-19 cases were admitted between 16 March 2020 and 30 November 2021, including 458 intensive care unit (ICU) cases. The results showed that the case fatality rate (CFR) increased with age, and females had a higher CFR. The median SOR of ICU cases was longer than that of non-ICU cases (27.6 vs. 17.0 days), while the median SOD was much shorter (6.9 vs. 8.4 days). The SOR and SOD in the Delta period were slightly shortened than the Alpha period. Age, cardiovascular diseases, chronic lung disease, diabetes, fever, breathing issues, and ICU admission were risk factors that were significantly associated with SOD (p < 0.001). A control measure, in-home quarantine, was found to be significantly associated with longer SOD (odds ratio = 9.49, p < 0.001). Infected vaccinated individuals had longer SOD than unvaccinated individuals, especially for cases that had received two vaccine doses (p < 0.001). Finally, an advice on getting full-dose vaccination is given specifically to individuals aged 20-59 years.

Assessing the impact of temperature and humidity exposures during early infection stages on case-fatality of COVID-19: A modelling study in Europe.

Background Although associations between key weather indicators (i.e. temperature and humidity) and COVID-19 mortality have been reported, the relationship between these exposures at different timings in early infection stages (from virus exposure up to a few days after symptom onset) and the probability of death after infection (also called case fatality rate, CFR) has yet to be determined. Methods We estimated the instantaneous CFR of eight European countries using Bayesian inference in conjunction with stochastic transmission models, taking account of delays in reporting the number of newly confirmed cases and deaths. The exposure-lag-response associations between fatality rate and weather conditions to which patients were exposed at different timings were obtained using distributed lag nonlinear models coupled with mixed-effect models. Results Our results show that the Odds Ratio (OR) of death is negatively associated with the temperature, with two maxima (OR = 1.29 (95% CI: 1.23, 1.35) at -0.1°C; OR = 1.12 (95% CI: 1.08, 1.16) at 0.1°C) occurring at the time of virus exposure and after symptom onset. Two minima (OR = 0.81 (95% CI: 0.71, 0.92) at 23.2°C; OR = 0.71 (95% CI: 0.63, 0.80) at 21.7°C) also occurred at these two distinct periods correspondingly. Low humidity (below 50%) during the early stages and high humidity (approximately 89%) after symptom onset were related to the lower fatality. Conclusion Environmental conditions may affect not only the initial viral load when patients are exposed to the virus, but also individuals' immune response around symptom onset. Warmer temperatures and higher humidity after symptom onset were linked to lower fatality.

Shorter Incubation Period among Unvaccinated Delta Variant Coronavirus Disease 2019 Patients in Japan.

Few studies have assessed incubation periods of the severe acute respiratory syndrome coronavirus 2 Delta variant. This study aimed to elucidate the transmission dynamics, especially the incubation period, for the Delta variant compared with non-Delta strains. We studied unvaccinated coronavirus disease 2019 patients with definite single exposure date from August 2020 to September 2021 in Japan. The incubation periods were calculated and compared by Mann-Whitney U test for Delta (with L452R mutation) and non-Delta cases. We estimated mean and percentiles of incubation period by fitting parametric distribution to data in the Bayesian statistical framework. We enrolled 214 patients (121 Delta and 103 non-Delta cases) with one specific date of exposure to the virus. The mean incubation period was 3.7 days and 4.9 days for Delta and non-Delta cases, respectively (p-value = 0.000). When lognormal distributions were fitted, the estimated mean incubation periods were 3.7 (95% credible interval (CI) 3.4-4.0) and 5.0 (95% CI 4.5-5.6) days for Delta and non-Delta cases, respectively. The estimated 97.5th percentile of incubation period was 6.9 (95% CI 5.9-8.0) days and 10.4 (95% CI 8.6-12.7) days for Delta and non-Delta cases, respectively. Unvaccinated Delta variant cases had shorter incubation periods than non-Delta variant cases.

Modelling the transmission dynamics of coronavirus disease 2019 with treatment as a control strategy: The case of India

This paper models the transmission dynamics of coronavirus disease 2019 (COVID-19) and its treatment based on the cases in India, by extending the classic SIR model to include exposed, asymptomatic, and treatment classes with a special focus to investigate the effect of ineffective treatment on the transmissibility of the infection with variation in the treatment initiation. The basic reproduction number was computed to understand the relative effect of early treatment initiation from the delayed treatment initiation on the transmissibility of the infection. With the estimated parameters obtained by faithfully fitting the simulation to the observed data, a global sensitivity analysis carried out indicated the treatment initiation to be one of the most influential parameters to infection control. With this concept, a further analysis revealed that an early treatment initiation can be a helpful control strategy on the transmissibility of the infection. However, for it to happen, an intervention such as proactively doing case finding is deemed important. Copyright © 2022 Inderscience Enterprises Ltd.

Viral Cultures for Coronavirus Disease 2019 Infectivity Assessment: A Systematic Review.

BACKGROUND: We aimed to review the evidence from studies relating severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) culture with the results of reverse-transcription polymerase chain reaction (RT-PCR) and other variables that may influence the interpretation of the test, such as time from symptom onset. METHODS: We searched LitCovid, medRxiv, Google Scholar, and the World Health Organization coronavirus disease 2019 (COVID-19) database for COVID-19 up to 10 September 2020. We included studies attempting to culture or observe SARS-CoV-2 in specimens with RT-PCR positivity. Studies were dual-extracted and the data summarized narratively by specimen type. Where necessary, we contacted corresponding authors of included papers for additional information. We assessed quality using a modified Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS 2) risk-of-bias tool. RESULTS: We included 29 studies reporting attempts at culturing, or observing tissue infection by, SARS-CoV-2 in sputum, nasopharyngeal or oropharyngeal, urine, stool, blood, and environmental specimens. The quality of the studies was moderate with lack of standardized reporting. The data suggest a relationship between the time from onset of symptom to the timing of the specimen test, cycle threshold (Ct), and symptom severity. Twelve studies reported that Ct values were significantly lower and log copies higher in specimens producing live virus culture. Two studies reported that the odds of live virus culture were reduced by approximately 33% for every 1-unit increase in Ct. Six of 8 studies reported detectable RNA for >14 days, but infectious potential declined after day 8 even among cases with ongoing high viral loads. Four studies reported viral culture from stool specimens. CONCLUSIONS: Complete live viruses are necessary for transmission, not the fragments identified by PCR. Prospective routine testing of reference and culture specimens and their relationship to symptoms, signs, and patient co-factors should be used to define the reliability of PCR for assessing infectious potential. Those with high Ct are unlikely to have infectious potential.

Earlier diagnosis improves COVID-19 prognosis: a nationwide retrospective cohort analysis.

BACKGROUND: Risk of adverse outcomes in COVID-19 patients by stratifying by the time from symptom onset to confirmed diagnosis status is still uncertain. METHODS: We included 1,590 hospitalized COVID-19 patients confirmed by real-time RT-PCR assay or high-throughput sequencing of pharyngeal and nasal swab specimens from 575 hospitals across China between 11 December 2019 and 31 January 2020. Times from symptom onset to confirmed diagnosis, from symptom onset to first medical visit and from first medical visit to confirmed diagnosis were described and turned into binary variables by the maximally selected rank statistics method. Then, survival analysis, including a log-rank test, Cox regression, and conditional inference tree (CTREE) was conducted, regarding whether patients progressed to a severe disease level during the observational period (assessed as severe pneumonia according to the Chinese Expert Consensus on Clinical Practice for Emergency Severe Pneumonia, admission to an intensive care unit, administration of invasive ventilation, or death) as the prognosis outcome, the dependent variable. Independent factors included whether the time from symptom onset to confirmed diagnosis was longer than 5 days (the exposure) and other demographic and clinical factors as multivariate adjustments. The clinical characteristics of the patients with different times from symptom onset to confirmed diagnosis were also compared. RESULTS: The medians of the times from symptom onset to confirmed diagnosis, from symptom onset to first medical visit, and from first medical visit to confirmed diagnosis were 6, 3, and 2 days. After adjusting for age, sex, smoking status, and comorbidity status, age [hazard ratio (HR): 1.03; 95% CI: 1.01-1.04], comorbidity (HR: 1.84; 95% CI: 1.23-2.73), and a duration from symptom onset to confirmed diagnosis of >5 days (HR: 1.69; 95% CI: 1.10-2.60) were independent predictors of COVID-19 prognosis, which echoed the CTREE models, with significant nodes such as time from symptom onset to confirmed diagnosis, age, and comorbidities. Males, older patients with symptoms such as dry cough/productive cough/shortness of breath, and prior COPD were observed more often in the patients who procrastinated before initiating the first medical consultation. CONCLUSIONS: A longer time from symptom onset to confirmed diagnosis yielded a worse COVID-19 prognosis.

Clinical performance of three fully automated anti-SARS-CoV-2 immunoassays targeting the nucleocapsid or spike proteins.

This study assesses the clinical performance of three anti-SARS-CoV-2 assays, namely EUROIMMUN anti-SARS-CoV-2 nucleocapsid (IgG) ELISA, Elecsys anti-SARS-CoV-2 nucleocapsid (total antibodies) assay, and LIAISON anti-SARS-CoV-2 spike proteins S1 and S2 (IgG) assay. One hundred and thirty-seven coronavirus disease 2019 (COVID-19) samples from 96 reverse-transcription polymerase chain reaction confirmed patients were chosen to perform the sensitivity analysis. Non-SARS-CoV-2 sera (n = 141) with a potential cross-reaction to SARS-CoV-2 immunoassays were included in the specificity analysis. None of these tests demonstrated a sufficiently high clinical sensitivity to diagnose acute infection. Fourteen days since symptom onset, we did not find any significant difference between the three techniques in terms of sensitivities. However, Elecsys performed better in terms of specificity. All three anti-SARS-CoV-2 assays had equivalent sensitivities 14 days from symptom onset to diagnose past-COVID-19 infection. We also confirmed that anti-SARS-CoV-2 determination before Day 14 is of less clinical interest.

Impact of the COVID-19 outbreak on hospitalizations and outcomes in patients with acute myocardial infarction in a Japanese Single Center.

There are a few Japanese data regarding the incidence and outcomes of acute myocardial infarction (AMI) after the coronavirus disease 2019 (COVID-19) outbreak. We retrospectively reviewed the data of AMI patients admitted to the Nihon University Itabashi Hospital after a COVID-19 outbreak in 2020 (COVID-19 period) and the same period from 2017 to 2019 (control period). The patients' characteristics, time course of admission, diagnosis, and treatment of AMI, and 30-day mortality were compared between the two period-groups for both ST-segment elevation myocardial infarction (STEMI) and non-STEMI (NSTEMI), respectively. The AMI inpatients decreased by 5.7% after the COVID-19 outbreak. There were no differences among most patient backgrounds between the two-period groups. For NSTEMI, the time from the symptom onset to admission was significantly longer, and that from the AMI diagnosis to the catheter examination tended to be longer during the COVID-19 period than the control period, but not for STEMI. The 30-day mortality was significantly higher during the COVID-19 period for NSTEMI (23.1% vs. 1.9%, P = 0.004), but not for STEMI (9.4% vs. 8.3%, P = 0.77). In conclusion, hospitalizations for AMI decreased after the COVID-19 outbreak. Acute cardiac care for STEMI and the associated outcome did not change, but NSTEMI outcome worsened after the COVID-19 outbreak, which may have been associated with delayed medical treatment due to the indirect impact of the COVID-19 pandemic.

Recovery scenario and immunity in COVID-19 disease: A new strategy to predict the potential of reinfection.

Background: The recent ongoing outbreak of coronavirus disease 2019 (COVID-19), still is an unsolved problem with a growing rate of infected cases and mortality worldwide. The novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is targeting the angiotensin-converting enzyme 2 (ACE2) receptor and mostly causes a respiratory illness. Although acquired and resistance immunity is one of the most important aspects of alleviating the trend of the current pandemic; however, there is still a big gap of knowledge regarding the infection process, immunopathogenesis, recovery, and reinfection. Aim of Review: To answer the questions regarding "the potential and probability of reinfection in COVID-19 infected cases" or "the efficiency and duration of SARS-CoV-2 infection-induced immunity against reinfection" we critically evaluated the current reports on SARS-CoV-2 immunity and reinfection with special emphasis on comparative studies using animal models that generalize their finding about protection and reinfection. Also, the contribution of humoral immunity in the process of COVID-19 recovery and the role of ACE2 in virus infectivity and pathogenesis has been discussed. Furthermore, innate and cellular immunity and inflammatory responses in the disease and recovery conditions are reviewed and an overall outline of immunologic aspects of COVID-19 progression and recovery in three different stages are presented. Finally, we categorized the infected cases into four different groups based on the acquired immunity and the potential for reinfection. Key Scientific Concepts of Review: In this review paper, we proposed a new strategy to predict the potential of reinfection in each identified category. This classification may help to distribute resources more meticulously to determine: who needs to be serologically tested for SARS-CoV-2 neutralizing antibodies, what percentage of the population is immune to the virus, and who needs to be vaccinated.

Time between Symptom Onset, Hospitalisation and Recovery or Death: Statistical Analysis of Belgian COVID-19 Patients.

There are different patterns in the COVID-19 outbreak in the general population and amongst nursing home patients. We investigate the time from symptom onset to diagnosis and hospitalization or the length of stay (LoS) in the hospital, and whether there are differences in the population. Sciensano collected information on 14,618 hospitalized patients with COVID-19 admissions from 114 Belgian hospitals between 14 March and 12 June 2020. The distributions of different event times for different patient groups are estimated accounting for interval censoring and right truncation of the time intervals. The time between symptom onset and hospitalization or diagnosis are similar, with median length between symptom onset and hospitalization ranging between 3 and 10.4 days, depending on the age of the patient (longest delay in age group 20-60 years) and whether or not the patient lives in a nursing home (additional 2 days for patients from nursing home). The median LoS in hospital varies between 3 and 10.4 days, with the LoS increasing with age. The hospital LoS for patients that recover is shorter for patients living in a nursing home, but the time to death is longer for these patients. Over the course of the first wave, the LoS has decreased.

Inference of COVID-19 epidemiological distributions from Brazilian hospital data.

Knowing COVID-19 epidemiological distributions, such as the time from patient admission to death, is directly relevant to effective primary and secondary care planning, and moreover, the mathematical modelling of the pandemic generally. We determine epidemiological distributions for patients hospitalized with COVID-19 using a large dataset (N = 21 000 - 157 000) from the Brazilian Sistema de Informação de Vigilância Epidemiológica da Gripe database. A joint Bayesian subnational model with partial pooling is used to simultaneously describe the 26 states and one federal district of Brazil, and shows significant variation in the mean of the symptom-onset-to-death time, with ranges between 11.2 and 17.8 days across the different states, and a mean of 15.2 days for Brazil. We find strong evidence in favour of specific probability density function choices: for example, the gamma distribution gives the best fit for onset-to-death and the generalized lognormal for onset-to-hospital-admission. Our results show that epidemiological distributions have considerable geographical variation, and provide the first estimates of these distributions in a low and middle-income setting. At the subnational level, variation in COVID-19 outcome timings are found to be correlated with poverty, deprivation and segregation levels, and weaker correlation is observed for mean age, wealth and urbanicity.

High clinical performance and quantitative assessment of antibody kinetics using a dual recognition assay for the detection of SARS-CoV-2 IgM and IgG antibodies.

OBJECTIVES: Several serological SARS-CoV-2 immunoassays have been developed recently but require external validation before widespread use. This study aims at assessing the analytical and clinical performance of the iFlash® anti-SARS-CoV-2 chemiluminescence assay for the detection of both IgM and IgG antibodies. The kinetics of the antibody response was also evaluated. DESIGN & METHODS: The precision, carry-over, linearity, limit of blank, detection and quantification were assessed. Sensitivity analysis was performed by using 178 sera collected from 154 RT-PCR confirmed COVID-19 patients. The specificity analysis was performed from 75 selected non-SARS-CoV-2 sera with a potential cross-reaction to the SARS-CoV-2 immunoassay. RESULTS: This iFlash® SARS-CoV-2 assay showed excellent analytical performance. After 2 weeks since symptom onset, the sensitivities for IgM and IgG were 62.2% (95% CI: 52.3-71.2%) and 92.9%% (95% CI: 85.7-96.7%), respectively by using the cut-off provided by the manufacturer. After cut-off optimization (i.e. >2.81 for IgM and >4.86 for IgG), the sensitivity for IgM and IgG were 81.6 (95% CI: 72.7-88.1%) and 95.9% (95% CI: 89.4-98.7%), respectively. Optimized cut-off for IgG improved the sensitivity to reach 100% (95%CI: 87.6-100) from 28 days since symptom onset. CONCLUSIONS: This study shows that the iFlash® SARS-CoV-2 assay from YHLO biotechnology, has satisfactory analytical performance. Nevertheless, the sensitivity of the IgM is limited for a proper clinical use compared to IgG. The determination of anti-SARS-CoV-2 IgG antibodies from 28 days since symptom onset was associated with high sensitivity, especially using optimized cut-offs (i.e. 100%).

Time from Symptom Onset to Hospitalisation of Coronavirus Disease 2019 (COVID-19) Cases: Implications for the Proportion of Transmissions from Infectors with Few Symptoms.

Interventions targeting symptomatic hosts and their contacts were successful in bringing the 2003 SARS pandemic under control. In contrast, the COVID-19 pandemic has been harder to contain, partly because of its wide spectrum of symptoms in infectious hosts. Current evidence suggests that individuals can transmit the novel coronavirus while displaying few symptoms. Here, we show that the proportion of infections arising from hosts with few symptoms at the start of an outbreak can, in combination with the basic reproduction number, indicate whether or not interventions targeting symptomatic hosts are likely to be effective. However, as an outbreak continues, the proportion of infections arising from hosts with few symptoms changes in response to control measures. A high proportion of infections from hosts with few symptoms after the initial stages of an outbreak is only problematic if the rate of new infections remains high. Otherwise, it can simply indicate that symptomatic transmissions are being prevented successfully. This should be considered when interpreting estimates of the extent of transmission from hosts with few COVID-19 symptoms.

Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20-28 January 2020.

A novel coronavirus (2019-nCoV) is causing an outbreak of viral pneumonia that started in Wuhan, China. Using the travel history and symptom onset of 88 confirmed cases that were detected outside Wuhan in the early outbreak phase, we estimate the mean incubation period to be 6.4 days (95% credible interval: 5.6-7.7), ranging from 2.1 to 11.1 days (2.5th to 97.5th percentile). These values should help inform 2019-nCoV case definitions and appropriate quarantine durations.