The secondary transmission pattern of COVID-19 based on contact tracing in Rwanda

Impact of disease severity, age, sex, comorbidity, and vaccination on secondary attack rates of SARS-CoV-2: a global systematic review and meta-analysis

BACKGROUND

Understanding the key drivers of SARS-CoV-2 transmission is essential for shaping effective public health strategies. However, transmission risk is subject to substantial heterogeneity related to disease severity, age, sex, comorbidities, and vaccination status in different population settings and regions. We aimed to quantify the impact of these factors on secondary attack rates (SARs) of SARS-CoV-2 across diverse population settings and regions, and identify key determinants of transmission to inform targeted interventions for improving global pandemic response.

METHODS

To retrieve relevant literature covering the duration of the COVID-19 pandemic, we searched Ovid MEDLINE, Ovid Embase, Web of Science, and the Cochrane COVID-19 Study Register between January 1, 2020 and January 18, 2024 to identify studies estimating SARs of SARS-CoV-2, defined as the proportion of close contacts infected. We pooled SAR estimates using a random-effects model with the Freeman-Tukey double arcsine transformation and derived Clopper-Pearson 95% confidence intervals (CIs). Risk of bias was assessed using a modified Newcastle-Ottawa scale. This study was registered with PROSPERO, CRD42024503782.

RESULTS

A total of 159 eligible studies, involving over 19 million close contacts and 6.8 million cases from 41 countries across five continents, were included in the analysis. SARs increased with disease severity in index cases, ranging from 0.10 (95% CI: 0.06-0.14; I2 = 99.65%) in asymptomatic infection to 0.15 (95% CI: 0.09-0.21; I2 = 92.49%) in those with severe or critical conditions. SARs by age were lowest at 0.20 (95% CI: 0.16-0.23; I2 = 99.44%) for close contacts under 18 years and highest at 0.29 (95% CI: 0.24-0.34; I2 = 99.65%) for index cases aged 65 years or older. Among both index cases and close contacts, pooled SAR estimates were highest for Omicron and lowest for Delta, and declined with increasing vaccine doses. Regionally, North America had the highest SAR at 0.27 (95% CI: 0.24-0.30; I2 = 99.31%), significantly surpassing SARs in Europe (0.19; 95% CI: 0.15-0.25; I2 = 99.99%), Southeast Asia (0.18; 95% CI: 0.13-0.24; I2 = 99.24%), and the Western Pacific (0.11; 95% CI: 0.08-0.15; I2 = 99.95%). Among close contacts with comorbidities, chronic lung disease and hypertension were associated with the highest SARs. No significant association was found between SARs and the sex of either index cases or close contacts.

CONCLUSIONS

Secondary attack rates varied substantially by demographic and regional characteristics of the studied populations. Our findings demonstrate the role of booster vaccinations in curbing transmission, underscoring the importance of maintaining population immunity as variants of SARS-CoV-2 continue to emerge. Effective pandemic responses should prioritise tailored interventions that consider population demographics and social dynamics across different regions.

Bayesian hierarchical spatiotemporal models for prediction of (under)reporting rates and cases: COVID-19 infection among the older people in the United States during the 2020-2022 pandemic

The gap between the reported and actual COVID-19 infection cases has been an issue of concern. Here, we present Bayesian hierarchical spatiotemporal disease mapping models for state-level predictions of COVID-19 infection risks and (under)reporting rates among people aged 65 and above during the first two years of the pandemic in the United States. With prior elicitation based on recent prevalence studies, the study suggests that the median state-level reporting rate of COVID-19 infection was 90% (interquartile range: [78%, 96%]). Our study uncovers spatiotemporal variations and dynamics in state-level infection risks and (under)reporting rates, suggesting time-varying associations between higher population density, higher percentage of minorities, and higher percentage of vaccination and increased risks of COVID-19 infection, as well as an association between more easily accessible tests and higher reporting rates. With sensitivity analyses, we highlight the impact and importance of incorporating covariates information and objective prior references for evaluating the issue of underreporting.

Estimating Asymptomatic and Symptomatic Transmission of the COVID-19 First Few Cases in Selenge Province, Mongolia

BACKGROUND

Following the first locally transmitted case in Sukhbaatar soum, Selenge Province, we aimed to investigate the ultimate scale of the epidemic in the scenario of uninterrupted transmission.

METHODS

This was a prospective case study following the locally modified WHO FFX cases generic protocol. A rapid response team collected data from November 14 to 29, 2020. We created a stochastic process to draw many transmission chains from this greater distribution to better understand and make inferences regarding the outbreak under investigation.

RESULTS

The majority of the cases involved household transmissions (35, 52.2%), work transmissions (20, 29.9%), index (5, 7.5%), same apartment transmissions (2, 3.0%), school transmissions (2, 3.0%), and random contacts between individuals transmissions (1, 1.5%). The posterior means of the basic reproduction number of both the asymptomatic casesR 0 Asy $$ {R}_0^{Asy} $$ and the presymptomatic casesR 0 Pre $$ {R}_0^{Pre} $$ (1.35 [95% CrI 0.88-1.86] and 1.29 [95% CrI 0.67-2.10], respectively) were lower than that of the symptomatic cases (2.00 [95% Crl 1.38-2.76]).

CONCLUSION

Our study highlights the heterogeneity of COVID-19 transmission across different symptom statuses and underscores the importance of early identification and isolation of symptomatic cases in disease control. Our approach, which combines detailed contact tracing data with advanced statistical methods, can be applied to other infectious diseases, facilitating a more nuanced understanding of disease transmission dynamics.

Third COVID-19 vaccine dose boosts antibody function in Rwandans with high HIV viral load

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) causing COVID-19 (coronavirus disease 2019) poses a greater health risk to immunocompromized individuals including people living with HIV (PLWH). However, most studies on PLWH have been conducted in higher-income countries. We investigated the post-vaccination antibody responses of PLWH in Rwanda by collecting peripheral blood from participants after receiving a second or third COVID-19 vaccine. Virus-binding antibodies as well as antibody neutralization ability against all major SARS-CoV-2 variants of concern were analyzed. We found that people with high HIV viral loads and two COVID-19 vaccine doses had lower levels of binding antibodies that were less virus neutralizing and less cross-reactive compared to control groups. A third vaccination increased neutralizing antibody titers. Our data suggest that people with high HIV viral loads require a third dose of vaccine to neutralize SARS-CoV-2 virus and new variants as they emerge.

Spatio-temporal dynamic of the COVID-19 epidemic and the impact of imported cases in Rwanda

INTRODUCTION

Africa was threatened by the coronavirus disease 2019 (COVID-19) due to the limited health care infrastructure. Rwanda has consistently used non-pharmaceutical strategies, such as lockdown, curfew, and enforcement of prevention measures to control the spread of COVID-19. Despite the mitigation measures taken, the country has faced a series of outbreaks in 2020 and 2021. In this paper, we investigate the nature of epidemic phenomena in Rwanda and the impact of imported cases on the spread of COVID-19 using endemic-epidemic spatio-temporal models. Our study provides a framework for understanding the dynamics of the epidemic in Rwanda and monitoring its phenomena to inform public health decision-makers for timely and targeted interventions.

RESULTS

The findings provide insights into the effects of lockdown and imported infections in Rwanda's COVID-19 outbreaks. The findings showed that imported infections are dominated by locally transmitted cases. The high incidence was predominant in urban areas and at the borders of Rwanda with its neighboring countries. The inter-district spread of COVID-19 was very limited due to mitigation measures taken in Rwanda.

CONCLUSION

The study recommends using evidence-based decisions in the management of epidemics and integrating statistical models in the analytics component of the health information system.

Spatial correlated incidence modeling with zero inflation

Disease mapping models have been popularly used to model disease incidence with spatial correlation. In disease mapping models, zero inflation is an important issue, which often occurs in disease incidence datasets with high proportions of zero disease count. It is originated from limited survey coverage or unadvanced testing equipment, which makes some regions have no observed patients. Then excessive zeros recorded in the disease incidence dataset would mess up the true distributions of disease incidence and lead to inaccurate estimates. To address this issue, a zero-inflated disease mapping model is developed in this work. In this model, a zero-inflated process using Bernoulli indicators is assumed to characterize whether the zero inflation occurs for each region. For regions without zero inflation, a coherent and generative disease mapping model is applied for mapping the spatially correlated disease incidence. Independent spatial random effects are incorporated in both processes to account for the spatial patterns of zero inflation and disease incidence. External covariates are also considered in both processes to better explain the disease count data. To estimate the model, a Markov chain Monte Carlo algorithm is proposed. We evaluate model performance via a variety of simulation experiments. Finally, a Lyme disease dataset of Virginia is analyzed to illustrate the application of the proposed model.

Spatial and spatio-temporal epidemiological approaches to inform COVID-19 surveillance and control: a systematic review of statistical and modelling methods in Africa

OBJECTIVE

Various studies have been published to better understand the underlying spatial and temporal dynamics of COVID-19. This review sought to identify different spatial and spatio-temporal modelling methods that have been applied to COVID-19 and examine influential covariates that have been reportedly associated with its risk in Africa.

DESIGN

Systematic review using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

DATA SOURCES

Thematically mined keywords were used to identify refereed studies conducted between January 2020 and February 2022 from the following databases: PubMed, Scopus, MEDLINE via Proquest, CINHAL via EBSCOhost and Coronavirus Research Database via ProQuest. A manual search through the reference list of studies was also conducted.

ELIGIBILITY CRITERIA FOR SELECTING STUDIES

Peer-reviewed studies that demonstrated the application of spatial and temporal approaches to COVID-19 outcomes.

DATA EXTRACTION AND SYNTHESIS

A standardised extraction form based on critical appraisal and data extraction for systematic reviews of prediction modelling studies checklist was used to extract the meta-data of the included studies. A validated scoring criterion was used to assess studies based on their methodological relevance and quality.

RESULTS

Among 2065 hits in five databases, title and abstract screening yielded 827 studies of which 22 were synthesised and qualitatively analysed. The most common socioeconomic variable was population density. HIV prevalence was the most common epidemiological indicator, while temperature was the most common environmental indicator. Thirteen studies (59%) implemented diverse formulations of spatial and spatio-temporal models incorporating unmeasured factors of COVID-19 and the subtle influence of time and space. Cluster analyses were used across seven studies (32%) to explore COVID-19 variation and determine whether observed patterns were random.

CONCLUSION

COVID-19 modelling in Africa is still in its infancy, and a range of spatial and spatio-temporal methods have been employed across diverse settings. Strengthening routine data systems remains critical for generating estimates and understanding factors that drive spatial variation in vulnerable populations and temporal variation in pandemic progression.

PROSPERO REGISTRATION NUMBER

CRD42021279767.

SMS-based digital health intervention in Rwanda's home-based care program for remote management of COVID-19 cases and contacts: A qualitative study of sustainability and scalability

Background

COVID-19 pandemic resulted in unprecedented global health challenges. Rwanda identified its first COVID-19 case on March 14, 2020 and subsequently introduced Home-Base Care (HBC) Program in August 2020 following community transmission of the virus and to alleviate logistical and financial strain on the healthcare system. Cases and contacts eligible for HBC were remotely supported by WelTel, an SMS-based mHealth intervention that was successfully implemented before for HIV epidemic in Rwanda. Enrolled cases and contacts were supported and monitored daily via their cell and/or mobile phones until they complete isolation/quarantine period. This study explored the rationale, perspectives, and experiences of key informants (KIs) during the implementation WelTel's mHealth tool for HBC in Rwanda.

Methods

Semi-structured one-on-one virtual interviews were conducted with KIs in this qualitative study. The KIs were classified into 2 major categories: (A) Senior staff including policymakers, directors, and senior managers; (B) Technical teams including case managers, and other staff supporting the implementation of WelTel (e.g., IT staff). Interviews were audio-recorded, transcribed, and analyzed in NVivo. Thematic analysis was conducted using a hybrid approach. A topic guide was developed using the Modified Consolidated Framework for Implementation Research and feedback from local stakeholders.

Results

7 KIs were interviewed. Five themes emerged following thematic analysis including: SMS-Based mHealth for Home-Isolation; Facilitators for Intervention Adoption; Barriers for Intervention Adoption; Infection prevention and control for Home-Isolation; and SMS-Based mHealth for Future Pandemics and Epidemics. Based on interviews, strong political commitment and advanced digital infrastructure were major facilitators for adopting WelTel for HBC. A major barrier to adopting WelTel was identified as technical-based issues. This was followed by local communication culture. All participates agreed on the significance of using WelTel to improve access and adherence to infection prevention and control measures, understand transmission dynamics, and inform public health decision-making regarding HBC.

Conclusions

Rwanda successfully adopted WelTel for supporting and monitoring COVID-19 cases and contacts in home-isolation and the implementation was instrumental to the country's effort to manage the pandemic. Experiences and perspectives of cases and contacts enrolled into WelTel must be explored to understand the appropriateness and effectiveness of the intervention.

Association Between Population-Level Factors and Household Secondary Attack Rate of SARS-CoV-2: A Systematic Review and Meta-analysis

Background

Accurate estimation of household secondary attack rate (SAR) is crucial to understand the transmissibility of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The impact of population-level factors, such as transmission intensity in the community, on SAR estimates is rarely explored.

Methods

In this study, we included articles with original data to compute the household SAR. To determine the impact of transmission intensity in the community on household SAR estimates, we explored the association between SAR estimates and the incidence rate of cases by country during the study period.

Results

We identified 163 studies to extract data on SARs from 326 031 cases and 2 009 859 household contacts. The correlation between the incidence rate of cases during the study period and SAR estimates was 0.37 (95% CI, 0.24-0.49). We found that doubling the incidence rate of cases during the study period was associated with a 1.2% (95% CI, 0.5%-1.8%) higher household SAR.

Conclusions

Our findings suggest that the incidence rate of cases during the study period is associated with higher SAR. Ignoring this factor may overestimate SARs, especially for regions with high incidences, which further impacts control policies and epidemiological characterization of emerging variants.

Household Transmission of SARS-CoV-2 in Bhutan

Introduction

The transmission trend of SARS-CoV-2 is continuously evolving. Understanding the dynamics in different settings is crucial for any effective containment measures. We aimed to study the characteristics of household transmission of SARS-CoV-2 in Bhutanese households by determining the transmissibility within household contacts of confirmed COVID-19 index cases and their factors of infectivity.

Methods

We conducted a retrospective observational study on household transmission in 306 household contacts of 93 COVID-19 positive index cases diagnosed from April 16, 2021, to June 30, 2021. A pro forma was used to collect data on the epidemiological, demographic, and clinical profile of all recruited individuals. Secondary attack rates (SAR) were calculated, and risk factors for transmission were estimated.

Results

180 of 306 household contacts developed secondary household transmission (SAR 58.8%; 95% CI: 53.2-64.2). The median age of household contacts was 22 years. The median household size was 4 (mean 4.3 ± 2.199) members. Contacts exposed to adult index cases (aPR 1; 95% CI 1, 1.02, p = 0.01) and vaccinated index cases (uPR 0.41, 95% CI 0.25, 0.66, p < 0.001) had a higher SAR and prevalence of secondary infections.

Conclusions

Our findings suggest substantial evidence of secondary infections among household contacts, especially in the context of public health mandated lockdowns. Aggressive early contact tracing and case identification with subsequent case isolation from other household members remains a crucial step in preventing secondary transmission.

Assessment of the Impact of COVID-19 on Operations of Local Businesses and Level of Enforcement of Public Health Safety Measure within Business Premises: A Quantitative Study of Businesses in Huye-Rwanda

The impact of COVID-19 has been felt across all sectors, from transportation, education, and public works to the daily operations of businesses like selling, retailing, and so forth. The business sector is among those badly affected, especially micro, small, and medium enterprises. The understanding of ground prevailing conditions is key in driving informed policies that would have meaningful impact on society with regard to overcoming the effects of the virus. Hence, this work is an attempt to report the real ground statistics and necessity of technological support with the goal of submitting a report of recommended policies to the concerned authorities. In this direction, this work presents the outcome of a survey conducted to assess the impact of COVID-19 on operations of micro, small, and medium enterprises and also to find out the interventions put in place around business environments so as to enforce adherence to COVID-19 health safety measures. The survey was part of a study to develop automated IoT-powered technological solutions that would help to enforce proper mask wearing in indoor environments and also observance of social distance requirements within business premises. A customized questionnaire was designed to capture data on various aspects central to the focus of the study. The study was carried out in the month of May 2021, in the Huye district of Rwanda. According to the survey findings, the major challenges faced by businesses due to COVID-19 include failure by clients to settle bills, reduced ability to expand investment, difficulty in accessing inputs domestically, lower domestic sales to consumers, and lower domestic sales to businesses. The results also reveal some positive points that most businesses were found to have: hand washing points, hand sanitizer dispensers, and mechanisms to enforce social distance between customer and customer and also customer and front desk worker. In a nutshell, this work is unique in terms of (1) the customized questionnaire about Rwanda’s needs, (2) field visit-based data collection for accurate data, and (3) including an assessment of the importance of technological intervention for better handling of public safety, especially in the MSME business sector.

A network meta-analysis of secondary attack rates of COVID-19 in different contact environments

As the corona virus disease 2019 (COVID-19) pandemic continues around the world, understanding the transmission characteristics of COVID-19 is vital for prevention and control. We conducted the first study aiming to estimate and compare the relative risk of secondary attack rates (SARs) of COVID-19 in different contact environments. Until 26 July 2021, epidemiological studies and cluster epidemic reports of COVID-19 were retrieved from SCI, Embase, PubMed, CNKI, Wanfang and CBM in English and Chinese, respectively. Relative risks (RRs) were estimated in pairwise comparisons of SARs between different contact environments using the frequentist NMA framework, and the ranking of risks in these environments was calculated using the surface under the cumulative ranking curve (SUCRA). Subgroup analysis was performed by regions. Thirty-two studies with 68 260 participants were identified. Compared with meal or gathering, transportation (RR 10.55, 95% confidence interval (CI) 1.43-77.85), medical care (RR 11.68, 95% CI 1.58-86.61) and work or study places (RR 10.15, 95% CI 1.40-73.38) had lower risk ratios for SARs. Overall, the SUCRA rankings from the highest to the lowest were household (95.3%), meal or gathering (81.4%), public places (58.9%), daily conversation (50.1%), transportation (30.8%), medical care (18.2%) and work or study places (15.3%). Household SARs were significantly higher than other environments in the subgroup of mainland China and sensitive analysis without small sample studies (<100). In light of the risks, stratified personal protection and public health measures need to be in place accordingly, so as close contacts categorising and management.

Factors Associated With Household Transmission of SARS-CoV-2: An Updated Systematic Review and Meta-analysis

Importance

A previous systematic review and meta-analysis of household transmission of SARS-CoV-2 that summarized 54 published studies through October 19, 2020, found an overall secondary attack rate (SAR) of 16.6% (95% CI, 14.0%-19.3%). However, the understanding of household secondary attack rates for SARS-CoV-2 is still evolving, and updated analysis is needed.

Objective

To use newly published data to further the understanding of SARS-CoV-2 transmission in the household.

Data Sources

PubMed and reference lists of eligible articles were used to search for records published between October 20, 2020, and June 17, 2021. No restrictions on language, study design, time, or place of publication were applied. Studies published as preprints were included.

Study Selection

Articles with original data that reported at least 2 of the following factors were included: number of household contacts with infection, total number of household contacts, and secondary attack rates among household contacts. Studies that reported household infection prevalence (which includes index cases), that tested contacts using antibody tests only, and that included populations overlapping with another included study were excluded. Search terms were SARS-CoV-2 or COVID-19 with secondary attack rate, household, close contacts, contact transmission, contact attack rate, or family transmission.

Data Extraction and Synthesis

Meta-analyses were performed using generalized linear mixed models to obtain SAR estimates and 95% CIs. The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline was followed.

Main Outcomes and Measures

Overall household SAR for SARS-CoV-2, SAR by covariates (contact age, sex, ethnicity, comorbidities, and relationship; index case age, sex, symptom status, presence of fever, and presence of cough; number of contacts; study location; and variant), and SAR by index case identification period.

Results

A total of 2722 records (2710 records from database searches and 12 records from the reference lists of eligible articles) published between October 20, 2020, and June 17, 2021, were identified. Of those, 93 full-text articles reporting household transmission of SARS-CoV-2 were assessed for eligibility, and 37 studies were included. These 37 new studies were combined with 50 of the 54 studies (published through October 19, 2020) from our previous review (4 studies from Wuhan, China, were excluded because their study populations overlapped with another recent study), resulting in a total of 87 studies representing 1 249 163 household contacts from 30 countries. The estimated household SAR for all 87 studies was 18.9% (95% CI, 16.2%-22.0%). Compared with studies from January to February 2020, the SAR for studies from July 2020 to March 2021 was higher (13.4% [95% CI, 10.7%-16.7%] vs 31.1% [95% CI, 22.6%-41.1%], respectively). Results from subgroup analyses were similar to those reported in a previous systematic review and meta-analysis; however, the SAR was higher to contacts with comorbidities (3 studies; 50.0% [95% CI, 41.4%-58.6%]) compared with previous findings, and the estimated household SAR for the B.1.1.7 (α) variant was 24.5% (3 studies; 95% CI, 10.9%-46.2%).

Conclusions and Relevance

The findings of this study suggest that the household remains an important site of SARS-CoV-2 transmission, and recent studies have higher household SAR estimates compared with the earliest reports. More transmissible variants and vaccines may be associated with further changes.