Epidemiology and transmission dynamics of COVID-19 in two Indian states

An observational study on imported COVID-19 cases in Hong Kong during mandatory on-arrival hotel quarantine

Background

Hong Kong enforced stringent travel restrictions during the COVID-19 pandemic. Understanding the characteristics of imported COVID-19 cases is important for establishing evidence-based control measures.

Methods

Retrospective cohort study summarising the characteristics of imported cases detected in Hong Kong between 13 November 2020 and 31 January 2022, when compulsory quarantine was implemented.

Findings

A total of 2269 imported COVID-19 cases aged 0-85 years were identified, of which 48.6 % detected on arrival. A shorter median delay from arrival to isolation was observed in Delta and Omicron cases (3 days) than in ancestral strain and other variants cases (12 days; p < 0.001). Lower Ct values at isolation were observed in Omicron cases than in ancestral strain or other variants cases. No Omicron cases were detected beyond 14 days after arrival. Cases detected after 14 days of quarantine (n=58, 2.6 %) were more likely asymptomatic at isolation and had higher Ct value during isolation, some of them indicating re-positivity or post-arrival infections.

Conclusions

Testing inbound travellers at arrival and during quarantine can detect imported cases early, but may not prevent all COVID-19 introductions into the community. Public health measures should be adapted in response to the emergence of SARS-CoV-2 variants based on evidence from ongoing surveillance.

Impact of waning immunity against SARS-CoV-2 severity exacerbated by vaccine hesitancy

The SARS-CoV-2 pandemic has generated a considerable number of infections and associated morbidity and mortality across the world. Recovery from these infections, combined with the onset of large-scale vaccination, have led to rapidly-changing population-level immunological landscapes. In turn, these complexities have highlighted a number of important unknowns related to the breadth and strength of immunity following recovery or vaccination. Using simple mathematical models, we investigate the medium-term impacts of waning immunity against severe disease on immuno-epidemiological dynamics. We find that uncertainties in the duration of severity-blocking immunity (imparted by either infection or vaccination) can lead to a large range of medium-term population-level outcomes (i.e. infection characteristics and immune landscapes). Furthermore, we show that epidemiological dynamics are sensitive to the strength and duration of underlying host immune responses; this implies that determining infection levels from hospitalizations requires accurate estimates of these immune parameters. More durable vaccines both reduce these uncertainties and alleviate the burden of SARS-CoV-2 in pessimistic outcomes. However, heterogeneity in vaccine uptake drastically changes immune landscapes toward larger fractions of individuals with waned severity-blocking immunity. In particular, if hesitancy is substantial, more robust vaccines have almost no effects on population-level immuno-epidemiology, even if vaccination rates are compensatorily high among vaccine-adopters. This pessimistic scenario for vaccination heterogeneity arises because those few individuals that are vaccine-adopters are so readily re-vaccinated that the duration of vaccinal immunity has no appreciable consequences on their immune status. Furthermore, we find that this effect is heightened if vaccine-hesitants have increased transmissibility (e.g. due to riskier behavior). Overall, our results illustrate the necessity to characterize both transmission-blocking and severity-blocking immune time scales. Our findings also underline the importance of developing robust next-generation vaccines with equitable mass vaccine deployment.

Prevalence, Outcomes, and Predictors of Prolonged Corrected QT Interval in Hydroxychloroquine-Naïve Hospitalized COVID-19 Patients

The studies regarding prevalence, outcomes, and predictors of prolonged corrected QT (QTc) among COVID-19 patients not on QTc-prolonging medication are not available in the literature. In this retrospective cohort study, the QTc of 295 hospital-admitted COVID-19 patients was analyzed and its association with in-hospital mortality was determined. The QTc was prolonged in 14.6% (43/295) of the study population. Prolonged QTc was seen in patients with older age (P = 0.018), coronary artery disease (P = 0.001), congestive heart failure (P = 0.042), elevated N-terminal-pro-B-type natriuretic peptide (NT-ProBNP) (P < 0.0001), and on remdesivir (P = 0.046). No episode of torsades de pointes arrhythmia or any arrhythmic death was observed among patients with prolonged QTc. The mortality was significantly high in patients with prolonged QTc (P = 0.003). The multivariate logistic regression analysis showed coronary artery disease (odds ratio (OR): 4.153, 95% CI 1.37-14.86; P = 0.013), and NT-ProBNP (ng/L) (OR: 1.000, 95% CI 1.000-1.000; P = 0.007) as predictors of prolonged QTc. The prolonged QTc was associated with the worst in-hospital survival (p by log-rank 0.001). A significant independent association was observed between prolonged QTc and in-hospital mortality in multivariate cox-regression analysis (adjusted hazard ratio: 3.861; (95% CI 1.719-6.523), P < 0.0001). QTc was found to be a marker of underlying comorbidities among COVID-19 patients. Prolonged QTc in hospitalized COVID-19 patients was independently associated with in-hospital mortality.

A capacity-building intervention for parents of children with disabilities in rural South India

BACKGROUND

A disability service organization piloted a parent capacity-building intervention for parents of children with developmental disabilities in rural South India.

AIMS

To examine the impact of this parent capacity-building group intervention on parent empowerment, peer support, social inclusion, advocacy skills, and the factors influencing these outcomes.

METHODS AND PROCEDURES

A qualitative study recruited 37 participants from 17 parent groups through convenience sampling. Six focus groups occurred six months post the start of this intervention and explored these parents' experiences with the groups and their perceived impacts.

OUTCOMES AND RESULTS

Qualitative analysis yielded four main themes and corresponding sub-themes: peer support (feeling peaceful and supported, building self-efficacy), social inclusion (space to share, acceptance and identity), knowledge sharing (increasing awareness, accepting advice), and advocacy (building confidence, making requests). Participation in parent groups provided participants with opportunities to find peer support, utilize knowledge sharing, feel socially included, and build advocacy skills.

CONCLUSIONS AND IMPLICATIONS

This study provides a greater understanding of the impact and benefits of parent capacity-building interventions in low-resource settings. Results will improve this intervention and guide other organizations in creating similar programs.

WHAT THIS PAPER ADDS

This paper adds perspectives of parents who are caregivers of children with developmental disabilities in rural South India. More specifically, this paper highlights the impact of a parent-focused intervention in group settings in both rural and urban areas. Parent support group interventions are not common in India and low- and middle-income countries and there is a paucity of literature describing these interventions and their impact. In this study, parents described a need for multifaceted interventions to support their child in the community. These parent groups provided space for caregivers of children with developmental disabilities to make connections, feel validated, and grow confidence to utilize new knowledge or advice shared by other parents to further enhance their lives. Further, parent-group settings provide opportunities to build advocacy skills through timely discussions. Parents reported an increase in feelings of acceptance within the group itself but not within the wider community. This highlights the need for involving the wider community in interventions to promote integration for families with children with disabilities.

Cardiac troponin in hospitalized COVID-19 patients: Incidence, predictors, and outcomes

BACKGROUND

The incidence, predictors, and association of cardiac troponin with mortality in hospitalized COVID-19 were not adequately studied in the past and were also not reported from an Indian hospital.

METHODS

In this retrospective cohort study, the cardiac troponin of 240 hospitalized COVID-19 patients was measured. The incidence, predictors, and association of elevated cardiac troponin with in-hospital mortality were determined among hospitalized COVID-19 patients.

RESULTS

The cardiac troponin was elevated in 12.9% (31/240) of the patients. The troponin was elevated in the patients in the older age group (64 years vs. 55 years, p = .002), severe COVID-19 illness (SpO2 < 90%) (93.5% vs. 60.8%, p < .001), low arterial oxygen saturation (SpO2) (80% vs. 88%, p = .001), and low PaO2/FiO2 ratio (p < .0001). The patients with elevated cardiac troponin had elevated total leukocyte counts (TLC) (p = .001), liver enzyme (p = .025), serum creatinine (p = .011), N-terminal-Pro Brain natriuretic peptide (p < .0001), and d-dimer (p < .0001). The majority of the patients with elevated cardiac troponin were admitted to the intensive care unit (90.3% vs. 51.2%; p < .0001), were on a ventilator (61.3% vs. 21.5%; p < .0001), and had higher mortality (64.5% vs. 19.6%; p < .0001). The Kaplan-Meir survival analysis showed that the patients with elevated troponin had worse survival (p log-rank<.0001). Age, NT-ProBNP, d-dimer, and ventilator were the predictors of elevated troponin in multivariate logistic regression analysis. The Cox-regression analysis showed a significant association between elevated cardiac troponin and in-hospital mortality (adjusted hazard ratio 2.13; 95% confidence interval [CI] 1.145-3.97; p = .017). Two-thirds (65%) of patients with elevated cardiac troponin died during their hospital stay.

CONCLUSIONS

COVID-19 patients with elevated cardiac troponin had severe COVID illness, were more commonly admitted to an intensive care unit, were on a ventilator, and had high in-hospital mortality.

Comparing lagged impacts of mobility changes and environmental factors on COVID-19 waves in rural and urban India: a Bayesian spatiotemporal modelling study

Previous research in India has identified urbanisation, human mobility and population demographics as key variables associated with higher district level COVID-19 incidence. However, the spatiotemporal dynamics of mobility patterns in rural and urban areas in India, in conjunction with other drivers of COVID-19 transmission, have not been fully investigated. We explored travel networks within India during two pandemic waves using aggregated and anonymized weekly human movement datasets obtained from Google, and quantified changes in mobility before and during the pandemic compared with the mean baseline mobility for the 8-week time period at the beginning of 2020. We fit Bayesian spatiotemporal hierarchical models coupled with distributed lag non-linear models (DLNM) within the integrated nested Laplace approximate (INLA) package in R to examine the lag-response associations of drivers of COVID-19 transmission in urban, suburban, and rural districts in India during two pandemic waves in 2020-2021. Model results demonstrate that recovery of mobility to 99% that of pre-pandemic levels was associated with an increase in relative risk of COVID-19 transmission during the Delta wave of transmission. This increased mobility, coupled with reduced stringency in public intervention policy and the emergence of the Delta variant, were the main contributors to the high COVID-19 transmission peak in India in April 2021. During both pandemic waves in India, reduction in human mobility, higher stringency of interventions, and climate factors (temperature and precipitation) had 2-week lag-response impacts on the R t of COVID-19 transmission, with variations in drivers of COVID-19 transmission observed across urban, rural and suburban areas. With the increased likelihood of emergent novel infections and disease outbreaks under a changing global climate, providing a framework for understanding the lagged impact of spatiotemporal drivers of infection transmission will be crucial for informing interventions.

Household Transmission Dynamics of Asymptomatic SARS-CoV-2-Infected Children: A Multinational, Controlled Case-Ascertained Prospective Study

BACKGROUND

Asymptomatic SARS-CoV-2 infection in children is highly prevalent but its acute and chronic implications have been minimally described.

METHODS

In this controlled case-ascertained household transmission study, we recruited asymptomatic children <18 years with SARS-CoV-2 nucleic acid testing performed at 12 tertiary care pediatric institutions in Canada and the United States. We attempted to recruit all test-positive children and 1 to 3 test-negative, site-matched controls. After 14 days' follow-up we assessed the clinical (ie, symptomatic) and combined (ie, test-positive, or symptomatic) secondary attack rates (SARs) among household contacts. Additionally, post-COVID-19 condition (PCC) was assessed in SARS-CoV-2-positive participating children after 90 days' follow-up.

RESULTS

A total of 111 test-positive and 256 SARS-CoV-2 test-negative asymptomatic children were enrolled between January 2021 and April 2022. After 14 days, excluding households with co-primary cases, the clinical SAR among household contacts of SARS-CoV-2-positive and -negative index children was 10.6% (19/179; 95% CI: 6.5%-16.1%) and 2.0% (13/663; 95% CI: 1.0%-3.3%), respectively (relative risk = 5.4; 95% CI: 2.7-10.7). In households with a SARS-CoV-2-positive index child, age <5 years, being pre-symptomatic (ie, developed symptoms after test), and testing positive during Omicron and Delta circulation periods (vs earlier) were associated with increased clinical and combined SARs among household contacts. Among 77 asymptomatic SARS-CoV-2-infected children with 90-day follow-up, 6 (7.8%; 95% CI: 2.9%-16.2%) reported PCC.

CONCLUSIONS

Asymptomatic SARS-CoV-2-infected children, especially those <5 years, are important contributors to household transmission, with 1 in 10 exposed household contacts developing symptomatic illness within 14 days. Asymptomatic SARS-CoV-2-infected children may develop PCC.

Dynamic of SARS-CoV-2 variants circulation in Tunisian pediatric population, during successive waves, from March 2020 to September 2022

The emergence of SARS-CoV-2 variants has led to several cases among children. However, limited information is available from North African countries. This study describes the SARS-CoV-2 strains circulating in Tunisian pediatric population during successive waves. A total of 447 complete sequences were obtained from individuals aged from 13 days to 18 years, between March 2020 and September 2022: 369 sequences generated during this study and 78 ones, available in GISAID, previously obtained from Tunisian pediatric patients. These sequences were compared with 354 and 274 ones obtained from Tunisian adults and a global dataset, respectively. The variant circulation dynamics of predominant variants were investigated during the study period using maximum-likelihood phylogenetic analysis. Among the studied population, adolescents were the predominant age group, comprising 55.26% of cases. Twenty-three lineages were identified; seven of which were not previously reported in Tunisia. Phylogenetic analysis showed a close relationship between the sequences from Tunisian adults and children. The connections of sequences from other countries were variable according to variants: close relationships were observed for Alpha, B1.160 and Omicron variants, while independent Tunisian clusters were observed for Delta and B.1.177 lineages. These findings highlight the pivotal role of children in virus transmission and underscore the impact of vaccination on virus spread. Vaccination of children, with booster doses, may be considered for better management of future emergences.

Inference under superspreading: Determinants of SARS-CoV-2 transmission in Germany

Superspreading, under-reporting, reporting delay, and confounding complicate statistical inference on determinants of disease transmission. A model that accounts for these factors within a Bayesian framework is estimated using German Covid-19 surveillance data. Compartments based on date of symptom onset, location, and age group allow to identify age-specific changes in transmission, adjusting for weather, reported prevalence, and testing and tracing. Several factors were associated with a reduction in transmission: public awareness rising, information on local prevalence, testing and tracing, high temperature, stay-at-home orders, and restaurant closures. However, substantial uncertainty remains for other interventions including school closures and mandatory face coverings. The challenge of disentangling the effects of different determinants is discussed and examined through a simulation study. On a broader perspective, the study illustrates the potential of surveillance data with demographic information and date of symptom onset to improve inference in the presence of under-reporting and reporting delay.

Secondary attack rates and determinants of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) household transmission in Pakistan: A case-ascertained prospective, longitudinal study

BACKGROUND

Households are considered ideal settings for studying the transmission dynamics of an infectious disease.

METHODS

A prospective study was conducted, based on the World Health Organization FFX protocol from October 2020 to January,2021. Household contacts of laboratory-confirmed index cases were followed up for their symptomatic history, nasal swabs for RT-PCR,and blood samples for anti-SARS CoV-2 antibodies were collected at enrollment and days 7, 14 and 28. We estimated secondary attack rate (SAR), effective household case cluster size and determinants of secondary infection among susceptible household contacts using multivariable logistic regression.

RESULTS

We enrolled 77 index cases and their 543 contacts. Out of these, 252 contacts were susceptible at the time of enrollment. There were 77 household clusters, out of which, transmission took place in 20 (25.9%) giving rise to 34 cases. The acquired secondary attack rate (SAR) was 14.0% (95% CI 9.0-18.0). The effective household case cluster size was 0.46 (95%CI 0.33,0.56). Reported symptoms of nausea and vomiting (aOR, 7.9; 95% CI, 1.4-45.5) and fatigue (aOR, 9.3; 95% CI, 3.8-22.7) were associated with SARS-CoV-2 transmission.

CONCLUSIONS

We observed a low SARS-CoV-2 secondary attack rate in the backdrop of high seroprevalence and asymptomatic transmission among households in Karachi, Pakistan.

Association of socio-demographic factors with clinical outcome among hospitalized patients in first and second waves of COVID-19 pandemic: Study from the developing world

Background

Recent disease resurgence in China indicates that corona virus infectious disease is still a pertinent public health problem. We stand at a juncture where we are still unsure about the initial dilemmas regarding its birth, therapies, and the emerging novel strains. Medical literature has focused on the clinical, laboratory, radiological, and therapeutic aspects of disease management. There is paucity of literature on the association between socio-demographic variables on disease severity and clinical outcome.

Materials and Methods

This retrospective observational study analyzing the socio-demographic variables was performed at a dedicated COVID care center in western Maharashtra, India. Electronic records of all individuals who were admitted to this hospital from July 29 2020, to June 14, 2021, and diagnosed COVID-19 positive by reverse transcriptase polymerase chain reaction (RT-PCR) were identified after due institutional ethical clearance. Patients admitted from July 29, 2020, to February 27, 2021, were categorized as patients presenting during the 'first wave of viral pandemic'. Those admitted from March 01, 2021, to June 14, 2021, have been included as patients admitted during 'second wave of viral pandemic'. The following outcome parameters were collected (presenting symptoms, duration of symptoms before the individual presented for diagnostic RT-PCR, total duration of symptoms, severity of disease at onset, duration of hospital stay, the final outcome (discharge/death) and Charlson's comorbidity index). The linear regression model was used to establish association between socio-demographic factors and disease severity at onset (mild/moderate/severe/critical).

Results

A total of 37033 patients were screened, and the positivity rate with RT-PCR was 16.99% (n = 6275) during the study period. Out of which 45% (n = 2824) of the patients had mild disease requiring home isolation and the remaining 55% of patients required admission. 1590 patients from the first wave and 910 from the second wave of COVID-19 were hospitalized and included in the study after exclusion. The mean age of patients in first wave was 49 years and that in second wave was 54 years with 77.6% and 70.6% males in two waves, respectively. The burden of critical cases was higher in second wave as computed to first wave (10% vs 8%). The second wave had more outreach in the rural population as compared to second one (17.8% vs 12.2%). The mean duration from the onset of symptoms to hospitalization was 03 and 04 days, respectively, in two waves. Mortality associated in two waves was 11.9% and 24%, respectively (P < 0.05). Higher Charlson's comorbidity index was associated with higher mortality, and the cumulative survival from urban area was more as compared to the rural population (log rank - 9.148, P = 0.0002).

Conclusion

The second COVID-19 wave had significantly higher case mortality. It affected elderly patients and those with rural background. The factors associated with higher mortality during COVID-19 pandemic were rural background, higher Charlson's comorbidity index and late presentation to the hospital. Ongoing vaccine campaigns, thus, should focus on rural areas and individuals with comorbidities especially in developing and least developed countries.

Lineage frequency time series reveal elevated levels of genetic drift in SARS-CoV-2 transmission in England

Genetic drift in infectious disease transmission results from randomness of transmission and host recovery or death. The strength of genetic drift for SARS-CoV-2 transmission is expected to be high due to high levels of superspreading, and this is expected to substantially impact disease epidemiology and evolution. However, we don't yet have an understanding of how genetic drift changes over time or across locations. Furthermore, noise that results from data collection can potentially confound estimates of genetic drift. To address this challenge, we develop and validate a method to jointly infer genetic drift and measurement noise from time-series lineage frequency data. Our method is highly scalable to increasingly large genomic datasets, which overcomes a limitation in commonly used phylogenetic methods. We apply this method to over 490,000 SARS-CoV-2 genomic sequences from England collected between March 2020 and December 2021 by the COVID-19 Genomics UK (COG-UK) consortium and separately infer the strength of genetic drift for pre-B.1.177, B.1.177, Alpha, and Delta. We find that even after correcting for measurement noise, the strength of genetic drift is consistently, throughout time, higher than that expected from the observed number of COVID-19 positive individuals in England by 1 to 3 orders of magnitude, which cannot be explained by literature values of superspreading. Our estimates of genetic drift suggest low and time-varying establishment probabilities for new mutations, inform the parametrization of SARS-CoV-2 evolutionary models, and motivate future studies of the potential mechanisms for increased stochasticity in this system.

Vaccination coverage against COVID-19 among rural population in Haryana, India: A cross-sectional study

BACKGROUND

Conducting a study in rural pre-dominant areas will help to understand the penetration of the vaccination campaign during the COVID-19 health crisis. This study aimed to investigate vaccination coverage against COVID-19 among the rural adult population in India and to identify factors associated with vaccination coverage.

METHODS

A population-based cross-sectional study was conducted among the rural population in one district of north India from January to February 2023. A semi-structured questionnaire was designed on the SurveyMonkey digital platform for interviewing the participants, which consisted of questions related to socio-demographic profile, health problems, vaccination status, types of vaccine, re-infection after vaccination, and functional difficulties. The data regarding infection with COVID-19 was collected based on self-reported positive testing for SARS-CoV 2 on RT-PCR.

FINDINGS

A total of 3700 eligible individuals were enumerated for the survey, out of which 2954 (79.8%) were interviewed. The infection rate of past COVID-19 infection, based on self-report of testing positive, was 6.2% (95%CI: 5.3-7.1). Covishield vaccine was received by most participants (81.3%, 2380) followed by Covaxin (12.3%, 361) and Pfizer manufactured vaccine (0.03,1). The coverage for first, second, and booster doses of the vaccine was 98.2% (2902), 94.8% (2802), and 10.7% (315) respectively. The risk of reinfection at 12 months or more among participants with two doses of vaccine was 1.6% (46/2802, 95%CI: 1.2-2.1). The coverage among those with severe functional difficulties was lesser as compared to those with some or no difficulties.

INTERPRETATION

Vaccination coverage against COVID-19 in rural Haryana, India is not dependent on factors like gender or occupation but is dependent on age and education. Although the full and partial vaccination coverage is high, the booster dose coverage is poor. In addition, the presence of severe disability was significantly associated with reduced vaccination coverage.

A Comparative Study of Deaths Due to the COVID-19 Pandemic During the First and Second Waves in a Tertiary Care Center of a Rural Area in South India

Background The coronavirus disease 2019 (COVID-19) pandemic affected life and livelihood worldwide, including India, with over five million deaths recorded over two years. In the present study, our objective was to analyze the COVID-19 deaths during the first and second waves in relation to demographic factors and comorbid conditions. Methods This was a hospital-based, retrospective comparative study of COVID-19 deaths that occurred in our hospital during the first and second waves of the COVID-19 pandemic. A total of 210 (6.69%) deaths recorded during both waves of the pandemic were analyzed. Microsoft Excel sheets (Microsoft Corporation, Redmond, WA, USA) were used to collect data from the medical records section, and the data were compiled. Descriptive statistics were used and analyzed using SPSS version 21 (IBM Corp., Armonk, NY, USA). Results Out of 3136 inpatients, mortality was 6.69% (n=210). Out of 210 deaths recorded in the study, 34 (2.25%) and 176 (10.7%) were during the first and second waves of the pandemic, respectively. The most common age group affected during the two waves was 50-75 years (67.6% & 47.7%; n=23 & n=84). People from urban (52.9%; n=18) and rural (67%; n=118) backgrounds were affected more during the first and second waves, respectively. Males were affected more (72.8%; n=153) in both waves. Age group (P=0.009) and locality (P=0.026) were statistically significant factors associated with mortality in the two COVID-19 waves. The time interval from admission in the hospital to death was less than seven days in both waves (70.5% & 69.8%; n=24 & n=123). A large number of subjects died after 48 hours of admission during both waves (70% (n=24 & n=124) in each wave). More than half of the subjects who died (52.9% (n=18) & 59% (n=104)) had comorbid conditions in both waves. Diabetes mellitus (17.6%; n=6) and hypertension (23.5%; n=8) were the most common comorbid conditions during the first wave of the pandemic while diabetes mellitus (30.6%; n=54) alone was the most common during the second wave. Conclusion The findings of this study stress the importance of considering demographic factors and geographic locations in understanding the impact of COVID-19, providing valuable inputs for public health interventions and resource allocation in response to similar pandemics.

Potential determinants of parental hesitancy to vaccinate their children against COVID-19 infection: a cross-sectional investigation

Coronavirus disease 2019 (COVID-19) vaccination hesitancy has emerged as a substantial concern among the adult population globally. However, limited evidence is available about parental hesitancy to vaccinate their children against COVID-19 within the Pakistani context. Thus, the present investigation aimed to assess parental attitudes, perceptions, and willingness regarding vaccination hesitancy and associated predictors of getting their children vaccinated against COVID-19. We conducted a cross-sectional population-based, self-administered online questionnaire in Punjab, Pakistan, on randomly selected parents between October 2022 and February 2023. The data were collected based on socio-demographics, attitudes, perceptions, and willingness of parents regarding COVID-19 vaccine hesitancy for their children. Adjusted odds ratios with 95% confidence intervals were estimated to identify the predictors of vaccine hesitancy. The findings demonstrated that among 1,478 participants, a total of 40% believed that the COVID-19 vaccine may pose a greater risk to children than adults, while 38% exhibited no concerns. Around 13% of children were not vaccinated in our study sample. More than half expressed hesitancy toward vaccination, and only 35.25% were inclined to get their children vaccinated in our study sample. In addition, only 16% of the parents believed that the COVID-19 vaccination may cause an alteration in their children's DNA. A similar proportion of parents were aware of the significance of getting their children vaccinated and expressed their willingness to vaccinate their children to prevent the COVID-19 infection. However, a higher odds ratio was observed in females with a higher educational background and those in the healthcare profession. In conclusion, healthcare awareness-supporting programs for educating parents should be designed and implemented. These insights might aid in the development of strategies to eradicate barriers in existing coronavirus vaccination programs and may vaccinate a larger child population to reduce the adverse consequences of the pandemic.

Risk factors of early mortality in COVID-19 patients in Indonesia: A retrospective cohort study in a provincial referral hospital of Aceh

Some of coronavirus disease 2019 (COVID-19) patients died after being hospitalized and early mortality is a matter of concern during the pandemic; therefore, it is critical to determine which patients are the most vulnerable of having early mortality. The aim of this study was to determine the risk factors for early mortality among hospitalized COVID-19 patients in Indonesia. A retrospective cohort study was conducted on hospitalized COVID-19 patients from July 2020 to September 2021 at Dr. Zainoel Abidin Hospital, Banda Aceh, Indonesia. Demographic data, clinical characteristics, laboratory findings, and mortality were collected. Early mortality was defined as a death before seven days of the hospitalization. Multivariate regression analysis was employed to determine the risk factors associated with early mortality. We included the data of 624 COVID-19 patients who died during the study period. More than half of the patients were male and aged over 50 years old. The average hospitalization period was 10 days and most patients had more than two comorbidities. Chronic lung disease was the most common comorbidity (46.0%) followed by respiratory disease (26.8%) and heart disease (14.3%). Multiple comorbidities and elevated D-dimers exceeding 3376.92 ng/mL were associated with early mortality with OR: 7.029; 95%CI: 2.02-24.43 and OR: 1.000085, 95%CI: 1.000028-1.000142, respectively. In conclusion, early mortality in COVID-19 patients was associated with having multiple comorbidities and elevated D-dimer level. Therefore, it is crucial to assess the presence of comorbidities and routine laboratory test while managing COVID-19 patients in order to prevent the early mortality.

Neutralization of SARS-CoV-2 Omicron BQ.1, BQ.1.1 and XBB.1 variants following SARS-CoV-2 infection or vaccination in children

Emergence of highly transmissible Omicron subvariants led to increased SARS-CoV-2 infection and disease in children. However, minimal knowledge exists regarding the neutralization capacity against circulating Omicron BA.4/BA.5, BA.2.75, BQ.1, BQ.1.1 and XBB.1 subvariants following SARS-CoV-2 vaccination in children versus during acute or convalescent COVID-19, or versus multisystem inflammatory syndrome (MIS-C). Here, we evaluate virus-neutralizing capacity against SARS-CoV-2 variants in 151 age-stratified children ( <5, 5-11, 12-21 years old) hospitalized with acute severe COVID-19 or MIS-C or convalescent mild (outpatient) infection compared with 62 age-stratified vaccinated children. An age-associated effect on neutralizing antibodies is observed against SARS-CoV-2 following acute COVID-19 or vaccination. The primary series BNT162b2 mRNA vaccinated adolescents show higher vaccine-homologous WA-1 neutralizing titers compared with <12 years vaccinated children. Post-infection antibodies did not neutralize BQ.1, BQ.1.1 and XBB.1 subvariants. In contrast, monovalent mRNA vaccination induces more cross-neutralizing antibodies in young children <5 years against BQ.1, BQ.1.1 and XBB.1 variants compared with ≥5 years old children. Our study demonstrates that in children, infection and monovalent vaccination-induced neutralization activity is low against BQ.1, BQ.1.1 and XBB.1 variants. These findings suggest a need for improved SARS-CoV-2 vaccines to induce durable, more cross-reactive neutralizing antibodies to provide effective protection against emerging variants in children.

Clinical characteristics and predictors of COVID-19 in a community sample from urban areas of Chennai, Southern India

In early 2020, with the arrival of the first case of COVID-19 in India, the laboratory at The Tamil Nadu Dr. MGR Medical University was recognized as a national testing site and received samples from two zones of Greater Chennai Corporation. This descriptive study analyzed the testing outcomes, along with demographics, self-reported symptoms, potential exposure to COVID-19 that were recorded in Sample Report Forms between June and September 2020. Nasopharygeal/oropharyngeal swabs were tested for SARS CoV-2 by RT-PCR Test. Of the 18,082 samples that were tested, 18% (3267) received a COVID-19 positive RT-PCR result for COVID-19. Among the COVID-19 positives, 40.9% (1336) were females (p < 0.000). Individuals in the age groups 21-30 and 31-40 years included the largest number (767, 23.48% each) of COVID-19 positive cases. The largest number of cases were from those who were classified as Severe Acute Respiratory Illness (SARI) or Influenza Like Illness (ILI) (1657, 50.7%) followed by those who reported direct contact with a COVID-19 lab confirmed case (1163, 35.6%). Among those with symptoms, 1791 (28.9%) tested COVID-19 positive compared to 1476 who were COVID-19 positive and asymptomatic (p < 0.001). Main symptoms were cough (32.1%), fever (48.3%), body ache (21.04%) and sore throat (30.60%). In multivariable analysis, history of SARI/ILI, contact with a confirmed case and having fever, cough and sore throat were the main predictors of being COVID-19 positive. Therefore, clinical and demographic characteristics correlated with COVID-19 positivity. And classification of patients based on self-reported symptoms and risk categories offers a model to prioritize testing and vaccination efforts.

Analysis of the Economic Burden of COVID-19 on the Workers of a Teaching Hospital in the Centre of Italy: Changes in Productivity Loss and Healthcare Costs Pre and Post Vaccination Campaign

Introduction: Following the concerning levels of spread and severity of the infection, on 11 March 2020, the World Health Organisation declared the COVID-19 outbreak a pandemic. In response to the pandemic, governments adopted several mitigation strategies. The pandemic posed a great threat to the Italian healthcare workforce (HW), with Italy being one of the hardest-hit countries. The aim of this study is to estimate the economic burden of COVID-19 on the workforce of a teaching hospital in Central Italy. Two periods are compared: 1 March 2020-9 February 2021 vs. 10 February 2021-31 March 2022. Methods: This study is conducted from a societal perspective. The database (n = 3298) of COVID-19-confirmed cases among the HW was obtained from the occupational health office of the hospital. The first entry on the database refers to 1 March 2020. Cost data were used to assess the economic burden of COVID-19 on the hospital workforce. They include two main groups: hourly salaries and medical expenses. The cost of productivity loss, hospital admission, at-home treatments, and contact tracing and screening tests were computed for the first and second periods of the analysis. Results: The total economic burden during the first period is estimated to be around EUR 3.8 million and in the second period EUR 4 million. However, the average cost per person is smaller in the second period (EUR 1561.78) compared to the first one (EUR 5906). In both periods, the cost of productivity loss is the largest component of the economic burden (55% and 57%). The cost of hospital admission decreased by more than 60% in the second period. Conclusion: Outcomes of the analysis suggest that the economic burden of COVID-19 on the HW is higher in the first period of analysis compared to the second period. The main reason could be identified in the shift from more severe and critical confirmed cases to more asymptomatic, mild, and moderate cases. The causes of this shift are not easily detectable. Vaccination, variants of the virus, and an individual's determinants of health could all be causes of the decrease in the economic burden of COVID-19 on the HW. COVID-19 can generate a high economic burden on healthcare workers and, more generally, on HWs. However, a comprehensive estimate of the economic burden of the pandemic needs to integrate the mental health repercussions and the long-term COVID-19 that will become evident in the coming years.

Dynamics in a behavioral-epidemiological model for individual adherence to a nonpharmaceutical intervention

The SARS-CoV-2 pandemic has highlighted the importance of behavioral drivers in epidemic dynamics. With the relaxation of mandated nonpharmaceutical interventions (NPIs) formerly in place to decrease transmission, such as mask-wearing or social distancing, adherence to an NPI is now the result of individual decision-making. To study these coupled dynamics, we embed a game-theoretic model for individual NPI adherence within an epidemiological model. When the disease is endemic, we find that our model has multiple (but none concurrently stable) equilibria: one each with zero, complete, or partial NPI adherence. Surprisingly, for the equilibrium with partial NPI adherence, the number of infections is independent of the transmission rate. Therefore, in that regime, a change in the rate of pathogen transmission, e.g., due to another (mandated) NPI or a new variant, has no effect on endemic infection levels. On the other hand, we show that vaccination successfully decreases endemic infection levels, and, unexpectedly, also reduces the number of susceptibles at equilibrium when there is partial adherence. From a game-theoretic perspective, we find that highly effective NPIs lead at most to partial adherence. As this effectiveness decreases, partially effective NPIs initially lead to increases in population-level adherence, especially if the risk is high enough. However, a completely ineffective NPI results in no adherence. Furthermore, we identify parameter regions where the individual incentives may not align with those of society as a whole. Overall, our findings illustrate complexities that can arise due to behavioral-epidemiological feedback and suggest appropriate measures to avoid more pessimistic population-level outcomes.

J. S, Meena S, Kumar R, Kaur R, Bairwa M, Kant S, Misra P, Rai SK, Ahmad M, Rahman A. Household transmission investigation for Corona Virus Disease 2019 (COVID-19) in a rural and urban population of north India

BACKGROUND

Transmissibility within closed settings, such as households, can provide a strategic way to characterize the virus transmission patterns because the denominator can be well defined. We aimed to characterize the household transmission of Severe Acute Respiratory Syndrome Coronavirus (SARS CoV-2) and its associated risk factors.

METHODS

This prospective case-ascertained study was conducted among the household contacts of laboratory-confirmed SARS CoV-2 cases residing in Ballabgarh, Haryana. We enrolled 148 index cases and their 645 household contacts between December 16, 2020 and June 24, 2021. We defined household contact as any person who had resided in the same household as a confirmed COVID-19 case. Baseline data collection and sample collection for real time- reverse transcriptase polymerase chain reaction (RT-PCR) and IgM/IgG against SARS CoV-2 were done on day 1 visit, and followed for a period of 28 days. RT-PCR was repeated on day 14 or whenever the contact is symptomatic and blood sample for serology was repeated on day 28. We estimated household secondary infection rate (SIR) and other epidemiological indicators-median incubation period and serial interval. We employed binomial logistic regression to quantify risk factors associated with infection.

RESULTS

The household SIR was 30.5% (95% CI: 27.1-34.1%). The secondary clinical attack rate was 9.3% (95% CI: 7.2-11.8). The risk factors that showed higher susceptibility to infection were household contacts who were the primary care giver of the case, whose index cases were symptomatic, those with underlying medical conditions, those living in overcrowded households, who were sharing toilet with the index cases and also who were not wearing a mask when coming in contact with the case. The median (IQR) incubation period was 4 days (4, 5), mean (SD) serial interval 6.4 (±2.2) days, and median (IQR) serial interval 5 days (5, 7).

CONCLUSION

Households favour secondary transmission of SARS CoV- 2, hence, index cases are recommended to self-isolate and wear masks; and household contacts to follow strict COVID infection control measures within households when a family member is infected.

Replicating superspreader dynamics with compartmental models

Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.

Estimating age-stratified transmission and reproduction numbers during the early exponential phase of an epidemic: A case study with COVID-19 data

In a pending pandemic, early knowledge of age-specific disease parameters, e.g., susceptibility, infectivity, and the clinical fraction (the fraction of infections coming to clinical attention), supports targeted public health responses like school closures or sequestration of the elderly. The earlier the knowledge, the more useful it is, so the present article examines an early phase of many epidemics, exponential growth. Using age-stratified COVID-19 case counts collected in Canada, China, Israel, Italy, the Netherlands, and the United Kingdom before April 23, 2020, we present a linear analysis of the exponential phase that attempts to estimate the age-specific disease parameters given above. Some combinations of the parameters can be estimated by requiring that they change smoothly with age. The estimation yielded: (1) the case susceptibility, defined for each age-group as the product of susceptibility to infection and the clinical fraction; (2) the mean number of transmissions of infection per contact within each age-group; and (3) the reproduction number of infection within each age-group, i.e., the diagonal of the age-stratified next-generation matrix. Our restriction to data from the exponential phase indicates the combinations of epidemic parameters that are intrinsically easiest to estimate with early age-stratified case counts. For example, conclusions concerning the age-dependence of case susceptibility appeared more robust than corresponding conclusions about infectivity. Generally, the analysis produced some results consistent with conclusions confirmed much later in the COVID-19 pandemic. Notably, our analysis showed that in some countries, the reproduction number of infection within the half-decade 70-75 was unusually large compared to other half-decades. Our analysis therefore could have anticipated that without countermeasures, COVID-19 would spread rapidly once seeded in homes for the elderly.

Lessons from COVID-19 for rescalable data collection

Novel data and analyses have had an important role in informing the public health response to the COVID-19 pandemic. Existing surveillance systems were scaled up, and in some instances new systems were developed to meet the challenges posed by the magnitude of the pandemic. We describe the routine and novel data that were used to address urgent public health questions during the pandemic, underscore the challenges in sustainability and equity in data generation, and highlight key lessons learnt for designing scalable data collection systems to support decision making during a public health crisis. As countries emerge from the acute phase of the pandemic, COVID-19 surveillance systems are being scaled down. However, SARS-CoV-2 resurgence remains a threat to global health security; therefore, a minimal cost-effective system needs to remain active that can be rapidly scaled up if necessary. We propose that a retrospective evaluation to identify the cost-benefit profile of the various data streams collected during the pandemic should be on the scientific research agenda.

Mortality in Two Waves of COVID-19: A Comparative Analysis of a Tertiary Care Hospital in India

Background COVID-19 has spread as two distinct surges of cases in many countries. Several countries have reported differences in disease severity and mortality in the two waves. Objective Compare the in-hospital mortality in the two COVID-19 waves at a tertiary care hospital in India. Methods We conducted a retrospective data collection. Distinct periods of surges in cases and admissions were defined as the first wave spanning from March 2020 to December 2020 and the second wave from April 2021 to June 21, 2021. The primary outcome of this study was to compare mortality rates in terms of total hospital mortality rate (TMR) and case fatality rate (CFR). Results Mortality rates of wave 2 were approximately 10 times that of wave 1 (TMR of 20.3% in wave 2 versus 2.4% in wave 1 and CFR of 1.5% versus 17.7% in wave 1 and 2, respectively). Mortalities in wave 2 had a larger proportion of severe disease at presentation, faster progression of symptoms to death, and more patients without any chronic comorbid condition dying due to the direct effect of COVID-19 acute respiratory distress syndrome (ARDS). Conclusion Our data matches the worldwide reported pooled hospital mortality figures and shows the comparative difference in disease severity between the two waves.

SARS-CoV-2 transmission patterns in educational settings during the Alpha wave in Reggio-Emilia, Italy

Different monitoring and control policies have been implemented in schools to minimize the spread of SARS-CoV-2. Transmission in schools has been hard to quantify due to the large proportion of asymptomatic carriers in young individuals. We applied a Bayesian approach to reconstruct the transmission chains between 284 SARS-CoV-2 infections ascertained during 87 school outbreak investigations conducted between March and April 2021 in Italy. Under the policy of reactive quarantines, we found that 42.5% (95%CrI: 29.5-54.3%) of infections among school attendees were caused by school contacts. The mean number of secondary cases infected at school by a positive individual during in-person education was estimated to be 0.33 (95%CrI: 0.23-0.43), with marked heterogeneity across individuals. Specifically, we estimated that only 26.0% (95%CrI: 17.6-34.1%) of students and school personnel who tested positive during in-person education caused at least one secondary infection at school. Positive individuals who attended school for at least 6 days before being isolated or quarantined infected on average 0.49 (95%CrI: 0.14-0.83) secondary cases. Our findings provide quantitative insights on the contribution of school transmission to the spread of SARS-CoV-2 in young individuals. Identifying positive cases within 5 days after exposure to their infector could reduce onward transmission at school by at least 30%.

An adaptive testing strategy for efficient utilization of healthcare resources during an epidemic

Lockdowns are found to be effective against rapidly spreading epidemics like COVID-19. Two downsides to strategies rooted in social distancing and lockdowns are that they adversely affect the economy and prolong the duration of the epidemic. The extended duration observed in these strategies is often due to the under-utilization of medical facilities. Even though an under-utilized health care system is preferred over an overwhelmed one, an alternate strategy could be to maintain medical facilities close to their capacity, with a factor of safety. We explore the practicality of this alternate mitigation strategy and show that it can be achieved by varying the testing rate. We present an algorithm to calculate the number of tests per day to maintain medical facilities close to their capacity. We illustrate the efficacy of our strategy by showing that it reduced the epidemic duration by 40% in comparison to lockdown-based strategies.

Pediatric SARS-CoV-2 Seroprevalence, Oregon, USA, November 1, 2020-June 30, 2022

We estimated SARS-CoV-2 seroprevalence in children in Oregon, USA, at 6 time points. Seroprevalence increased linearly during November 2020-December 2021 and peaked in February 2022 at 38.8% (95% CI 32.8%-46.5%). We observed no increase in the seroprevalence trend after widespread school reopening. Seroprevalence estimates complement case-based cumulative incidence.

Medium-term scenarios of COVID-19 as a function of immune uncertainties and chronic disease

As the SARS-CoV-2 trajectory continues, the longer-term immuno-epidemiology of COVID-19, the dynamics of Long COVID, and the impact of escape variants are important outstanding questions. We examine these remaining uncertainties with a simple modelling framework that accounts for multiple (antigenic) exposures via infection or vaccination. If immunity (to infection or Long COVID) accumulates rapidly with the valency of exposure, we find that infection levels and the burden of Long COVID are markedly reduced in the medium term. More pessimistic assumptions on host adaptive immune responses illustrate that the longer-term burden of COVID-19 may be elevated for years to come. However, we also find that these outcomes could be mitigated by the eventual introduction of a vaccine eliciting robust (i.e. durable, transmission-blocking and/or 'evolution-proof') immunity. Overall, our work stresses the wide range of future scenarios that still remain, the importance of collecting real-world epidemiological data to identify likely outcomes, and the crucial need for the development of a highly effective transmission-blocking, durable and broadly protective vaccine.

The Role of Children in Household Transmission of SARS-CoV-2 Across Four Waves of the Pandemic

BACKGROUND

It is important to understand the dynamics of SARS-CoV-2 transmission in close-contact settings such as households. We hypothesized that children would most often acquire SARS-CoV-2 from a symptomatic adult caregiver.

METHODS

This prospective cohort study was conducted from April 2020 to July 2022 in a low-resource, urban settlement in Brazil. We recruited families who brought their children to a public clinic. We collected nasopharyngeal and oral swabs from household members and tracked symptoms and vaccination.

RESULTS

In total, 1256 participants in 298 households were tested for SARS-CoV-2. A total of 4073 RT-PCR tests were run with 893 SARS-CoV-2 positive results (21.9%). SARS-CoV-2 cases were defined as isolated cases (N = 158) or well-defined transmission events (N = 175). The risk of household transmission was lower if the index case was a child (OR: 0.3 [95% CI: 0.16-0.55], P < .001) or was vaccinated (OR: 0.29 [95% CI: 0.1-0.85], P = .024), and higher if the index was symptomatic (OR: 2.53 [95% CI: 1.51-4.26], P < .001). The secondary attack rate for child index cases to child contacts was 0.29, whereas the secondary attack rate for adult index cases to child contacts was 0.47 (P = .08).

CONCLUSIONS

In this community, children were significantly less infectious to their household contacts than adolescents or adults. Most children were infected by a symptomatic adult, usually their mother. There was a double benefit of vaccination as it protected the vaccine from severe illness and prevented onward transmission to household contacts. Our findings may also be valid for similar populations throughout Latin America.

COVID-19 Pandemic: Did Strict Mobility Restrictions Save Lives and Healthcare Costs in Maharashtra, India?

INTRODUCTION

Maharashtra, India, remained a hotspot during the COVID-19 pandemic. After the initial complete lockdown, the state slowly relaxed restrictions. We aim to estimate the lockdown's impact on COVID-19 cases and associated healthcare costs.

METHODS

Using daily case data for 84 days (9 March-31 May 2020), we modeled the epidemic's trajectory and predicted new cases for different phases of lockdown. We fitted log-linear models to estimate the growth rate, basic (R₀), daily reproduction number (R_e), and case doubling time. Based on pre-restriction and Phase 1 R₀, we predicted new cases for the rest of the restriction phases, and we compared them with the actual number of cases during each phase. Furthermore, using the published and gray literature, we estimated the costs and savings of implementing these restrictions for the projected period, and we performed a sensitivity analysis.

RESULTS

The estimated median R₀ during the different phases was 1.14 (95% CI: 0.85, 1.45) for pre-lockdown, 1.67 (95% CI: 1.50, 1.82) for phase 1 (strict mobility restrictions), 1.24 (95% CI: 1.12, 1.35) for phase 2 (extension of phase 1 with no restrictions on agricultural and essential services), 1.12 (95% CI: 1.01, 1.23) for phase 3 (extension of phase 2 with mobility relaxations in areas with few infections), and 1.05 (95% CI: 0.99, 1.123) for phase 4 (implementation of localized lockdowns in high-case-load areas with fewer restrictions on other areas), respectively. The corresponding doubling time rate for cases (in days) was 17.78 (95% CI: 5.61, -15.19), 3.87 (95% CI: 3.15, 5.00), 10.37 (95% CI: 7.10, 19.30), 20.31 (95% CI: 10.70, 212.50), and 45.56 (95% CI: 20.50, -204.52). For the projected period, the cases could have reached 631,819 without the lockdown, as the actual reported number of cases was 64,975. From a healthcare perspective, the estimated total value of averted cases was INR 194.73 billion (USD 2.60 billion), resulting in net cost savings of 84.05%. The Incremental Cost-Effectiveness Ratio (ICER) per Quality Adjusted Life Year (QALY) for implementing the lockdown, rather than observing the natural course of the pandemic, was INR 33,812.15 (USD 450.83).

CONCLUSION

Maharashtra's early public health response delayed the pandemic and averted new cases and deaths during the first wave of the pandemic. However, we recommend that such restrictions be carefully used while considering the local socio-economic realities in countries like India.

Epidemiology of SARS-CoV-2 transmission and superspreading in Salt Lake County, Utah, March-May 2020

BACKGROUND

Understanding the drivers of SARS-CoV-2 transmission can inform the development of interventions. We evaluated transmission identified by contact tracing investigations between March-May 2020 in Salt Lake County, Utah, to quantify the impact of this intervention and identify risk factors for transmission.

METHODS

RT-PCR positive and untested symptomatic contacts were classified as confirmed and probable secondary case-patients, respectively. We compared the number of case-patients and close contacts generated by different groups, and used logistic regression to evaluate factors associated with transmission.

RESULTS

Data were collected on 184 index case-patients and up to six generations of contacts. Of 1,499 close contacts, 374 (25%) were classified as secondary case-patients. Decreased transmission odds were observed for contacts aged <18 years (OR = 0.55 [95% CI: 0.38-0.79]), versus 18-44 years, and for workplace (OR = 0.36 [95% CI: 0.23-0.55]) and social (OR = 0.44 [95% CI: 0.28-0.66]) contacts, versus household contacts. Higher transmission odds were observed for case-patient's spouses than other household contacts (OR = 2.25 [95% CI: 1.52-3.35]). Compared to index case-patients identified in the community, secondary case-patients identified through contract-tracing generated significantly fewer close contacts and secondary case-patients of their own. Transmission was heterogeneous, with 41% of index case-patients generating 81% of directly-linked secondary case-patients.

CONCLUSIONS

Given sufficient resources and complementary public health measures, contact tracing can contain known chains of SARS-CoV-2 transmission. Transmission is associated with age and exposure setting, and can be highly variable, with a few infections generating a disproportionately high share of onward transmission.

Attributed causes of excess mortality during the COVID-19 pandemic in a south Indian city

Globally, excess deaths during 2020-21 outnumbered documented COVID-19 deaths by 9.5 million, primarily driven by deaths in low- and middle-income countries (LMICs) with limited vital surveillance. Here we unravel the contributions of probable COVID-19 deaths from other changes in mortality related to pandemic control measures using medically-certified death registrations from Madurai, India-an urban center with well-functioning vital surveillance. Between March, 2020 and July, 2021, all-cause deaths in Madurai exceeded expected levels by 30% (95% confidence interval: 27-33%). Although driven by deaths attributed to cardiovascular or cerebrovascular conditions, diabetes, senility, and other uncategorized causes, increases in these attributions were restricted to medically-unsupervised deaths, and aligned with surges in confirmed or attributed COVID-19 mortality, likely reflecting mortality among unconfirmed COVID-19 cases. Implementation of lockdown measures was associated with a 7% (0-13%) reduction in all-cause mortality, driven by reductions in deaths attributed to injuries, infectious diseases and maternal conditions, and cirrhosis and other liver conditions, respectively, but offset by a doubling in cancer deaths. Our findings help to account for gaps between documented COVID-19 mortality and excess all-cause mortality during the pandemic in an LMIC setting.

Population density and SARS-CoV-2 pandemic: Comparing the geography of different waves in the Netherlands

The COVID-19 pandemic has boosted public and scholarly debate about the relationship between infectious disease and the urban. Cities are considered contagious because they are hubs in (inter)national networks and contain high densities of people. However, the role of the urban and population density in the spread of pathogens is complex and is mediated by the wider bio-social environment. This paper analyses the role of population density in the outbreak of COVID-19 in the densely and highly urbanised context of the Netherlands. It compares the geography of the different phases in the epidemic and assesses when and where density plays a role. Using municipal data on the rate of infections and hospitalisations, this paper reveals that spatial patterns differ substantially in time, which does not appear to be simple diffusion. Using panel regressions, it is demonstrated that population density plays a role in those stages in which containment and mitigation measures were least strict, while in periods of lockdown other factors such as household size are associated with higher infection rates. It concludes that lockdowns may have greater effect in urban areas as key urban elements are temporarily cancelled out.

Disproportionate impacts of COVID-19 in a large US city

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5-24.8%) infection rate and 29.4% (95% CrI: 28.0-31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3-12.0%] vs 25.1% [95% CrI: 23.7-26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49-57%] vs 28% [95% CrI: 27-30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

Household transmission dynamics of COVID-19 among residents of Delhi, India: a prospective case-ascertained study

Objective

The aim of this study was to observe the secondary infection rate and transmission dynamics of COVID-19 among household contacts, and their associations with various factors across four dimensions of interaction.

Methods

This was a case-ascertained study among unvaccinated household contacts of a laboratory-confirmed COVID-19 case in New Delhi between December 2020 and July 2021. For this study, 99 index cases and their 316 household contacts were interviewed and sampled (blood and oro-nasal swab) on days 1, 7, 14, and 28.

Results

The secondary infection rate among unvaccinated household contacts was 44.6% (95% confidence interval (CI) 39.1-50.1). The predictors of secondary infection among individual contact levels were: being female (odds ratio (OR) 2.13), increasing age (OR 1.01), symptoms at baseline (OR 3.39), and symptoms during follow-up (OR 3.18). Among index cases, age of the primary case (OR 1.03) and symptoms during follow-up (OR 6.29) were significantly associated with secondary infection. Among household-level and contact patterns, having more rooms (OR 4.44) and taking care of the index case (OR 2.02) were significantly associated with secondary infection.

Conclusion

A high secondary infection rate highlights the need to adopt strict measures and advocate COVID-19-appropriate behaviors. A targeted approach for higher-risk household contacts would efficiently limit infections among susceptible contacts.

Superspreading, overdispersion and their implications in the SARS-CoV-2 (COVID-19) pandemic: a systematic review and meta-analysis of the literature

BACKGROUND

A recurrent feature of infectious diseases is the observation that different individuals show different levels of secondary transmission. This inter-individual variation in transmission potential is often quantified by the dispersion parameter k. Low values of k indicate a high degree of variability and a greater probability of superspreading events. Understanding k for COVID-19 across contexts can assist policy makers prepare for future pandemics.

METHODS

A literature search following a systematic approach was carried out in PubMed, Embase, Web of Science, Cochrane Library, medRxiv, bioRxiv and arXiv to identify publications containing epidemiological findings on superspreading in COVID-19. Study characteristics, epidemiological data, including estimates for k and R0, and public health recommendations were extracted from relevant records.

RESULTS

The literature search yielded 28 peer-reviewed studies. The mean k estimates ranged from 0.04 to 2.97. Among the 28 studies, 93% reported mean k estimates lower than one, which is considered as marked heterogeneity in inter-individual transmission potential. Recommended control measures were specifically aimed at preventing superspreading events. The combination of forward and backward contact tracing, timely confirmation of cases, rapid case isolation, vaccination and preventive measures were suggested as important components to suppress superspreading.

CONCLUSIONS

Superspreading events were a major feature in the pandemic of SARS-CoV-2. On the one hand, this made outbreaks potentially more explosive but on the other hand also more responsive to public health interventions. Going forward, understanding k is critical for tailoring public health measures to high-risk groups and settings where superspreading events occur.

Reducing societal impacts of SARS-CoV-2 interventions through subnational implementation

To curb the initial spread of SARS-CoV-2, many countries relied on nation-wide implementation of non-pharmaceutical intervention measures, resulting in substantial socio-economic impacts. Potentially, subnational implementations might have had less of a societal impact, but comparable epidemiological impact. Here, using the first COVID-19 wave in the Netherlands as a case in point, we address this issue by developing a high-resolution analysis framework that uses a demographically stratified population and a spatially explicit, dynamic, individual contact-pattern based epidemiology, calibrated to hospital admissions data and mobility trends extracted from mobile phone signals and Google. We demonstrate how a subnational approach could achieve similar level of epidemiological control in terms of hospital admissions, while some parts of the country could stay open for a longer period. Our framework is exportable to other countries and settings, and may be used to develop policies on subnational approach as a better strategic choice for controlling future epidemics.

The effect of variation of individual infectiousness on SARS-CoV-2 transmission in households

Quantifying variation of individual infectiousness is critical to inform disease control. Previous studies reported substantial heterogeneity in transmission of many infectious diseases including SARS-CoV-2. However, those results are difficult to interpret since the number of contacts is rarely considered in such approaches. Here, we analyze data from 17 SARS-CoV-2 household transmission studies conducted in periods dominated by ancestral strains, in which the number of contacts was known. By fitting individual-based household transmission models to these data, accounting for number of contacts and baseline transmission probabilities, the pooled estimate suggests that the 20% most infectious cases have 3.1-fold (95% confidence interval: 2.2- to 4.2-fold) higher infectiousness than average cases, which is consistent with the observed heterogeneity in viral shedding. Household data can inform the estimation of transmission heterogeneity, which is important for epidemic management.

Risk factors for SARS-CoV-2 infection in primary and secondary school students and staff in England in the 2020/2021 school year: a longitudinal study

OBJECTIVES

Investigate risk factors for SARS-CoV-2 infections in school students and staff.

METHODS

In the 2020/2021 school year, we administered polymerase chain reaction, antibody tests, and questionnaires to a sample of primary and secondary school students and staff, with data linkage to COVID-19 surveillance. We fitted logistic regression models to identify the factors associated with infection.

RESULTS

We included 6799 students and 5090 staff in the autumn and 11,952 students and 4569 staff in the spring/summer terms. Infections in students in autumn 2020 were related to the percentage of students eligible for free school meals. We found no statistical association between infection risk in primary and secondary schools and reported contact patterns between students and staff in either period in our study. Using public transports was associated with increased risk in autumn in students (adjusted odds ratio = 1.72; 95% confidence interval 1.31-2.25) and staff. One or more infections in the same household during either period was the strongest risk factor for infection in students and more so among staff.

CONCLUSION

Deprivation, community, and household factors were more strongly associated with infection than contacts patterns at school; this suggests that the additional school-based mitigation measures in England in 2020/2021 likely helped reduce transmission risk in schools.

Extreme value modelling of SARS-CoV-2 community transmission using discrete generalized Pareto distributions

Superspreading has been suggested to be a major driver of overall transmission in the case of SARS-CoV-2. It is, therefore, important to statistically investigate the tail features of superspreading events (SSEs) to better understand virus propagation and control. Our extreme value analysis of different sources of secondary case data indicates that case numbers of SSEs associated with SARS-CoV-2 may be fat-tailed, although substantially less so than predicted recently in the literature, but also less important relative to SSEs associated with SARS-CoV. The results caution against pooling data from both coronaviruses. This could provide policy- and decision-makers with a more reliable assessment of the tail exposure to SARS-CoV-2 contamination. Going further, we consider the broader problem of large community transmission. We study the tail behaviour of SARS-CoV-2 cluster cases documented both in official reports and in the media. Our results suggest that the observed cluster sizes have been fat-tailed in the vast majority of surveyed countries. We also give estimates and confidence intervals of the extreme potential risk for those countries. A key component of our methodology is up-to-date discrete generalized Pareto models which allow for maximum likelihood-based inference of data with a high degree of discreteness.

Experiences, Challenges, and Lessons Learned During Implementation of a Remote Monitoring Program for Home-Isolated COVID-19 Patients in Chennai, India

During the early months of the COVID-19 pandemic in 2020, the majority of the identified COVID-19 patients in Chennai, a southern metropolitan city of India, presented as asymptomatic or with mild clinical illness. Providing facility-based care for these patients was not feasible in an overburdened health system. Thus, providing home-based clinical care for patients who were asymptomatic or with mild clinical illnesses was a viable solution. Because of the imminent possibility of worsening clinical conditions in home-isolated COVID-19 patients, continuous monitoring for red flag signs was essential. With growing evidence of the effectiveness of remote monitoring of patients, the Greater Chennai Corporation in partnership with the National Institute of Epidemiology conceptualized and implemented a remote monitoring program for home-isolated COVID-19 patients. The key steps used to develop the program were to (1) decentralize triage systems and establish a home-isolation protocol, (2) develop a remote monitoring platform and remote health care workforce, and (3) onboard patients and conduct remote hybrid monitoring. In this article, we share the pragmatic solutions, critical components of the systems and processes, lessons, and experiences in implementing a remote monitoring program for home-isolated COVID-19 patients in a large metropolitan setting.

Differences in Immune Responses in Individuals of Indian and European Origin: Relevance for the COVID-19 Pandemic

During the coronavirus disease 2019 (COVID-19) pandemic, large differences in susceptibility and mortality due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported between populations in Europe and South Asia. While both host and environmental factors (including Mycobacterium bovis BCG vaccination) have been proposed to explain this, the potential biological substrate of these differences is unknown. We purified peripheral blood mononuclear cells from individuals living in India and the Netherlands at baseline and 10 to 12 weeks after BCG vaccination. We compared chromatin accessibility between the two populations at baseline, as well as gene transcription profiles and cytokine production capacities upon stimulation. The chromatin accessibility of genes important for adaptive immunity was higher in the Indians than in the Europeans, while the latter had more accessible chromatin regions in genes of the innate immune system. At the transcriptional level, we observed that the Indian volunteers displayed a more tolerant immune response to stimulation, in contrast to a more exaggerated response in the Europeans. BCG vaccination strengthened the tolerance program in the Indians but not in the Europeans. These differences may partly explain the different impact of COVID-19 on the two populations. IMPORTANCE In this study, we assessed the differences in immune responses in individuals from India and Europe. This aspect is of great relevance, because of the described differences in morbidity and mortality between India and Europe during the pandemic. We found a significant difference in chromatin accessibility in immune cells from the two populations, followed by a more balanced and effective response in individuals from India. These exciting findings represent a very important piece of the puzzle for understanding the COVID-19 pandemic at a global level.

Model-based estimation of burden of COVID-19 with disability-adjusted life years and value of statistical life in West Bengal, India

OBJECTIVES

The COVID-19 pandemic has posed unprecedented challenges to health systems and populations, particularly in India. Comprehensive, population-level studies of the burden of disease could inform planning, preparedness and policy, but are lacking in India. In West Bengal, India, we conducted a detailed analysis of the burden caused by COVID-19 from its onset to 7 January 2022.

SETTING

Open-access, population-level and administrative data sets for West Bengal were used.

PRIMARY AND SECONDARY OUTCOME MEASURES

Disability-adjusted life years (DALYs), years of potential productive life lost (YPPLL), cost of productivity lost (CPL: premature mortality and absenteeism), years of potential life lost (YPLL), premature years of potential life lost, working years of potential life lost (WYPLL) and value of statistical life (VSL) were estimated across scenarios (21 for DALY and 3 each for YPLL and VSL) to evaluate the effects of different factors.

RESULTS

COVID-19 had a higher impact on the elderly population with 90.2% of deaths arising from people aged above 45. In males and females, respectively, DALYs were 190 568.1 and 117 310.0 years, YPPLL of the productive population was 28 714.7 and 16 355.4 years, CPL due to premature mortality was INR3 198 259 615.6 and INR583 397 335.1 and CPL due to morbidity was INR2 505 568 048.4 and INR763 720 886.1. For males and females, YPLL ranged from 189 103.2 to 272 787.5 years and 117 925.5 to 169 712.0 years for lower to higher age limits, and WYPLL was 54 333.9 and 30 942.2 years. VSL (INR million) for the lower, midpoint and upper life expectancies was 883 330.8; 882 936.4; and 880 631.3, respectively. Vaccination was associated with reduced mortality.

CONCLUSIONS

The losses incurred due to COVID-19 in terms of the computed estimates in West Bengal revealed a disproportionately higher impact on the elderly and males. Analysis of various age-gender subgroups enhances localised and targeted policymaking to minimise the losses for future pandemics.

COVID-19 prevalence and infection control practices among dentists in Andhra Pradesh State, India

BACKGROUND

The coronavirus 2019 (COVID-19) pandemic posed a new challenge not only to public health but also to the health care systems and dentists are one of the highly vulnerable health care professionals for COVID-19 infection.

OBJECTIVE

To assess the COVID-19 prevalence, associated factors, and infection control practices among dentists in Andhra Pradesh State, IndiaMETHODS:A cross-sectional web-based questionnaire survey was conducted among dentists in Andhra Pradesh state, India. 21-item pretested questionnaire was used for data collection between January 30, 2021 and February 21, 2021. 3700 dentists from the Andhra Pradesh state were selected from the Dentists Register of India through systematic random sampling method.

RESULTS

Out of 3700 dentists invited to participate in this study, responses from 1876 dentists were received with response rate of 51%. Prevalence of 8 among the study population was 9%. Patients were the primary source of infection for 60.5% of the COVID-19 positive study participants. 65.8% of total respondents using full face shield and two-third of them using N-95 or equivalent mask while providing dental care.

CONCLUSION

This study found a high prevalence rate of COVID 19 among the dentists. Among the associated factors, being into active practice during the pandemic was found to be statistically significant. This study recommend for additional infection control protocols specific to the COVID-19 pandemic.

Aerosol measurement identifies SARS-CoV 2 PCR positive adults compared with healthy controls

BACKGROUND

SARS-CoV-2 is spread primarily through droplets and aerosols. Exhaled aerosols are generated in the upper airways through shear stress and in the lung periphery by 'reopening of collapsed airways'. Aerosol measuring may detect highly contagious individuals ("super spreaders or super-emitters") and discriminate between SARS-CoV-2 infected and non-infected individuals. This is the first study comparing exhaled aerosols in SARS-CoV-2 infected individuals and healthy controls.

DESIGN

A prospective observational cohort study in 288 adults, comprising 64 patients testing positive by SARS CoV-2 PCR before enrollment, and 224 healthy adults testing negative (matched control sample) at the University Hospital Frankfurt, Germany, from February to June 2021. Study objective was to evaluate the concentration of exhaled aerosols during physiologic breathing in SARS-CoV-2 PCR-positive and -negative subjects. Secondary outcome measures included correlation of aerosol concentration to SARS-CoV-2 PCR results, change in aerosol concentration due to confounders, and correlation between clinical symptoms and aerosol.

RESULTS

There was a highly significant difference in respiratory aerosol concentrations between SARS-CoV-2 PCR-positive (median 1490.5/L) and -negative subjects (median 252.0/L; p < 0.0001). There were no significant differences due to age, sex, smoking status, or body mass index. ROC analysis showed an AUC of 0.8918.

CONCLUSIONS

Measurements of respiratory aerosols were significantly elevated in SARS-CoV-2 positive individuals, which helps to understand the spread and course of respiratory viral infections, as well as the detection of highly infectious individuals.

Pandemetrics: systematically assessing, monitoring, and controlling the evolution of a pandemic

The still ongoing pandemic of SARS-CoV-2 virus and COVID-19 disease, affecting the population worldwide, has demonstrated the need of more accurate methodologies for assessing, monitoring, and controlling an outbreak of such devastating proportions. Authoritative attempts have been made in traditional fields of medicine (epidemiology, virology, infectiology) to address these shortcomings, mainly by relying on mathematical and statistical modeling. However, here, we propose approaching the methodological work from a different, and to some extent alternative, standpoint. Applied systematically, the concepts and tools of statistical engineering and quality management, developed not only in healthcare settings, but also in other scientific contexts, can be very useful in assessing, monitoring, and controlling pandemic events. We propose a methodology based on a set of tools and techniques, formulas, graphs, and tables to support the decision-making concerning the management of a pandemic like COVID-19. This methodological body is hereby named Pandemetrics. This name intends to emphasize the peculiarity of our approach to measuring, and graphically presenting the unique context of the COVID-19 pandemic.

Long-Term Antibody Response to SARS-CoV-2 in Children

Almost 2 years into the pandemic and with vaccination of children significantly lagging behind adults, long-term pediatric humoral immune responses to SARS-CoV-2 are understudied. The C19.CHILD Hamburg (COVID-19 Child Health Investigation of Latent Disease) Study is a prospective cohort study designed to identify and follow up children and their household contacts infected in the early 2020 first wave of SARS-CoV-2. We screened 6113 children < 18 years by nasopharyngeal swab-PCR in a low-incidence setting after general lockdown, from May 11 to June 30, 2020. A total of 4657 participants underwent antibody testing. Positive tests were followed up by repeated PCR and serological testing of all household contacts over 6 months. In total, the study identified 67 seropositive children (1.44%); the median time after infection at first presentation was 83 days post-symptom onset (PSO). Follow-up of household contacts showed less than 100% seroprevalence in most families, with higher seroprevalence in families with adult index cases compared to pediatric index cases (OR 1.79, P = 0.047). Most importantly, children showed sustained seroconversion up to 9 months PSO, and serum antibody concentrations persistently surpassed adult levels (ratio serum IgG spike children vs. adults 90 days PSO 1.75, P < 0.001; 180 days 1.38, P = 0.01; 270 days 1.54, P = 0.001). In a low-incidence setting, SARS-CoV-2 infection and humoral immune response present distinct patterns in children including higher antibody levels, and lower seroprevalence in families with pediatric index cases. Children show long-term SARS-CoV-2 antibody responses. These findings are relevant to novel variants with increased disease burden in children, as well as for the planning of age-appropriate vaccination strategies.

Impact of contact rate on epidemic spreading in complex networks

Abstract

Contact reduction is an effective strategy to mitigate the spreading of epidemic. However, the existing reaction-diffusion equations for infectious disease are unable to characterize this effect. Thus, we here propose an extended susceptible-infected-recovered model by incorporating contact rate into the standard SIR model, and concentrate on investigating its impact on epidemic transmission. We analytically derive the epidemic thresholds on homogeneous and heterogeneous networks, respectively. The effects of contact rate on spreading speed, scale and outbreak threshold are explored on ER and SF networks. Simulations results show that epidemic dissemination is significantly mitigated when contact rate is reduced. Importantly, epidemic spreads faster on heterogeneous networks while broader on homogeneous networks, and the outbreak thresholds of the former are smaller.

Graphical abstract

Diminishing returns: Nudging Covid-19 prevention among Colombian young adults

Nonpharmaceutical interventions (NPIs) like social distancing, face masks, and handwashing will continue to be a frontline defense against Covid-19 for some time. But their effectiveness depends critically on compliance by young adults, who are most likely both to become infected and to infect others. We conducted a randomized controlled trial in Bogotá, Colombia, to assess the effectiveness of informational nudges emphasizing the private and public benefits of compliance on university students' concern about Covid-19, recent compliance with NPI recommendations, and intended future compliance. Although nudges boosted concern, they had limited effects on either recent or intended future compliance. We attribute these null results to high baseline levels of information about and compliance with NPIs, an informational diminishing returns scenario that is likely to be increasingly common globally.