Serial Interval Research Articles

Estimation Methods of Reproduction Numbers for Epidemics of Varying Strains of COVID-19

The estimation methods of reproduction numbers and serial intervals are important in the early stages of infectious diseases. During the COVID pandemic, China implemented a dynamic zero-COVID policy on the Chinese mainland until the end of 2022. This study compares three estimation methods of reproduction numbers on small-scale, short-duration COVID-19 epidemics in Fujian province. Basic reproduction numbers were investigated using a varying-strain model via a next-generation matrix method. Serial intervals were derived using the infector–infectee pairs of two epidemics from the Fujian Provincial Center for Disease Control and Prevention. Basic reproduction numbers were estimated using maximum likelihood estimation and an exponential growth method. The curves of the effective reproduction numbers of the three epidemics were plotted by utilizing daily cases and the EpiEstim R package. The spatial heterogeneity of infection cases was described using the Gini coefficient. This study provides significant insights on the estimation methods of reproduction numbers for policymakers in the local government. The results reveal that social contacts between infectors and susceptible individuals should be reduced to avoid an increase in deaths and to fight against the spread of infectious diseases.

Best practices for estimating and reporting epidemiological delay distributions of infectious diseases.

Epidemiological delays are key quantities that inform public health policy and clinical practice. They are used as inputs for mathematical and statistical models, which in turn can guide control strategies. In recent work, we found that censoring, right truncation, and dynamical bias were rarely addressed correctly when estimating delays and that these biases were large enough to have knock-on impacts across a large number of use cases. Here, we formulate a checklist of best practices for estimating and reporting epidemiological delays. We also provide a flowchart to guide practitioners based on their data. Our examples are focused on the incubation period and serial interval due to their importance in outbreak response and modeling, but our recommendations are applicable to other delays. The recommendations, which are based on the literature and our experience estimating epidemiological delay distributions during outbreak responses, can help improve the robustness and utility of reported estimates and provide guidance for the evaluation of estimates for downstream use in transmission models or other analyses.

Effectiveness of accelerated diagnostic protocols for reducing emergency department length of stay in patients presenting with chest pain: A systematic review and meta-analysis.

In recent years, there has been an increase in the use of accelerated diagnostic protocols (ADPs) and high-sensitivity troponin assays (hsTn) for the assessment of chest pain in emergency departments (EDs). This study aimed to quantitatively summarize the operational and clinical outcomes of ADPs implemented for patients with suspected cardiac chest pain. To be considered eligible for inclusion, studies must have implemented some form of ADP within the ED for evaluating adult (age ≥18 years) patients presenting with chest pain using Tn assays. The primary outcome was ED length of stay (LOS). Secondary outcomes included the proportion of patients admitted and the proportion with 30-day major adverse cardiac events (MACE). Thirty-seven articles involving 404,566 patients met the inclusion criteria, including five randomized controlled trials (RCTs) and 32 observational studies. A significant reduction in total ED LOS was reported in 22 observational studies and four RCTs. Emergency departments with longer baseline ED LOS showed significantly larger reductions in LOS after ADP implementation. This observed association persisted after adjusting for both the change in serial Tn measurement interval and transition from conventional Tn assay to an hsTn assay (β = -0.26; 95% CI, -0.43 to -0.10). Three studies reported an increase in the proportion of patients admitted after introducing an ADP, one of which was significant while 15 studies reported a significant decrease in admission proportion. There was moderate heterogeneity among the 13 studies that reported MACE proportions, with a non-significant pooled risk ratio of 0.95 (95% CI, 0.86-1.04). Implementation of ADPs for chest pain presentations decreases ED LOS, most noticeably within sites with a high baseline LOS; this decreased LOS is seen even in the absence of any change in troponin assay type. The decrease in LOS occurred alongside reductions in hospital admissions, while not increasing MACE. The observed benefits translated across multiple countries and health regions.

Refining Estimation of the Instantaneous Reproduction Number During Early Pandemic Stages: Addressing Case-Reporting Variability and Serial Interval Uncertainty.

During infectious disease outbreaks, estimates for the instantaneous reproduction number, R(t), are essential for understanding transmission dynamics. This study develops and analyzes new methodology to improve estimation of R(t) when observed case counts are subject to reporting patterns and available serial interval estimates are subject to uncertainty and non-representativeness. Specifically, we developed a Bayesian time-since-infection model with layers to adjust for reporting measurement error, integrate multiple candidate serial interval estimates, and estimate transmission with an autoregressive time-series model incorporating factors relevant to transmission. Additionally, we provide practical tools to identify reporting patterns and determine when to smooth case counts for more usable R(t) estimates. We evaluated model performance relative to widely adopted methodology by simulating outbreak data, finding improved R(t) estimation with the proposed methodology. We also used 2020 COVID-19 data to analyze transmission trends and predictors, identifying strong day-of-week and social distancing effects that subsequently reduced estimate volatility. In addition to new approaches for addressing serial interval uncertainty and incorporating transmission predictor information, this study provides an alternative approach for addressing case-reporting patterns without delaying detection or smoothing over relevant transmission signals. These tools and findings may be used or built upon for current and future outbreaks.

Heterotopic ossification following total hip arthroplasty. Which is the predominant risk factor: surgical approach or post-operative prophylaxis?

To investigate the impact of surgical approach and post-operative prophylaxis on heterotopic ossification (HO) development after total hip arthroplasty (THA). A retrospective analysis of 312 patients who underwent THA between January 2009 and April 2016. Patients were categorized by surgical approach (direct lateral or posterolateral), prosthesis type, and post-operative prophylaxis (Etoricoxib 60mg daily for two weeks). Two orthopaedic surgeons independently assessed radiographs at serial intervals, and HO was graded as per Brooker classification. Bivariate analysis and regression modelling were performed to assess the associations and confounding effects of different variables, RESULTS: Bivariate analysis identified factors correlated with higher HO incidence: absence of prophylaxis, older age, longer symptom evolution, and lower pre-surgery physical activity. Regression modelling showed a correlation between the direct-lateral approach, post-operative prophylaxis, symptom evolution, and higher HO incidence. Patients with longer symptom evolution before surgery and without post-operative prophylaxis are at higher risk of developing HO. While the direct lateral approach showed higher HO rates, the difference was insignificant. A two-week prophylactic regimen of Etoricoxib 60mg daily after THA effectively reduced HO formation. Pharmacological prophylaxis should be evaluated case-by-case, considering patient characteristics and risk factors.

Characteristics and predictors of Long Covid in children: a 3-year prospective cohort study

Children can develop Long Covid, however long term outcomes and their predictors are poorly described in these patients. The primary aim is to describe characteristics and predictors of Long Covid in children assessed in-clinics up to 36 months post-SARS-CoV-2 infection, as well as investigate the role of vaccines in preventing Long Covid, risk of reinfections and development of autoimmune diseases. Children aged 0-18 years old with confirmed SARS-CoV-2 infection were invited for a prospective follow-up assessment at a peadiatric post-covid clinic in Rome, Italy, at serial intervals (3-, 6-, 12-, 18-, 24- and 36-months post-infection onset, between 01/02/2020 and 28/02/2024). Long Covid was defined as persistence of otherwise unexplained symptoms for at least three months after initial infection. 1319 patients were initially included, 1296 reached the 3 months follow-up or more. Of the patients who underwent multiple follow-ups, 23.2% (301), 169 (13.2%), 89 (7.9%), 67 (6.1%), 47 (7.1%) were diagnosed with Long Covid at 3-6-12-18-24 months, respectively For the primary outcome of Long Covid at three months, age >12 years (P<0.001, OR 11.33, 95% CI 4.2; 15.15), comorbidities (P=0.008, OR 1.83, 95% CI 1.06; 2.44), being infected with original variants (P<0.001, OR 4.77, 95% CI 2.46; 14.47), female sex (P<0.001, OR 1.62, 95% CI 1.02; 1.89) were statistically significant risk factors. Age >12 years (P=0.002, OR 9.37, 95% CI 1.58; 8.64), and infection with original (P=0.012, OR 3.52, 95% CI 1.32; 8.64) and alfa (P<0.001, OR 4.09, 95% CI 2.01; 8.3) SARS-CoV-2 variants remained statistically significant risk factors for Long Covid duration for at least 18 months. Vaccination was associated with a lower risk of long covid at 3, 6 and 12 months for older children and a lower risk of reinfections. Being infected with the original SARS-CoV-2 variant was associated with a higher risk of new-onset autoimmune diseases ((P=0.035, 95% CI 1.12; 2.4). One patient was diagnosed with Long Covid after a re-infection. This is the longest follow-up study of children with SARS-CoV-2 infection, showing a significant and long-lasting burden of Long Covid in the pediatric population. Our findings highlight the urgent need of investing in pediatric Long Covid in order to find effective diagnostic and therapeutic approaches, as well can inform preventive strategies in case of future pandemics. This study has been funde by Pfizer non-competitive grant, granted to DB (#65925795).

Estimating the household secondary attack rate and serial interval of COVID-19 using social media

We propose a method to estimate the household secondary attack rate (hSAR) of COVID-19 in the United Kingdom based on activity on the social media platform X, formerly known as Twitter. Conventional methods of hSAR estimation are resource intensive, requiring regular contact tracing of COVID-19 cases. Our proposed framework provides a complementary method that does not rely on conventional contact tracing or laboratory involvement, including the collection, processing, and analysis of biological samples. We use a text classifier to identify reports of people tweeting about themselves and/or members of their household having COVID-19 infections. A probabilistic analysis is then performed to estimate the hSAR based on the number of self or household, and self and household tweets of COVID-19 infection. The analysis includes adjustments for a reluctance of Twitter users to tweet about household members, and the possibility that the secondary infection was not acquired within the household. Experimental results for the UK, both monthly and weekly, are reported for the period from January 2020 to February 2022. Our results agree with previously reported hSAR estimates, varying with the primary variants of concern, e.g. delta and omicron. The serial interval (SI) is based on the time between the two tweets that indicate a primary and secondary infection. Experimental results, though larger than the consensus, are qualitatively similar. The estimation of hSAR and SI using social media data constitutes a new tool that may help in characterizing, forecasting and managing outbreaks and pandemics in a faster, affordable, and more efficient manner.

Insights into COVID-19 epidemiology and control from temporal changes in serial interval distributions in Hong Kong.

The serial interval distribution is used to approximate the generation time distribution, an essential parameter to infer the transmissibility (${R}_t$) of an epidemic. However, serial interval distributions may change as an epidemic progresses. We examined detailed contact tracing data on laboratory-confirmed cases of COVID-19 in Hong Kong during the five waves from January 2020 to July 2022. We reconstructed the transmission pairs and estimated time-varying effective serial interval distributions and factors associated with longer or shorter intervals. Finally, we assessed the biases in estimating transmissibility using constant serial interval distributions. We found clear temporal changes in mean serial interval estimates within each epidemic wave studied and across waves, with mean serial intervals ranged from 5.5 days (95% CrI: 4.4, 6.6) to 2.7 (95% CrI: 2.2, 3.2) days. The mean serial intervals shortened or lengthened over time, which were found to be closely associated with the temporal variation in COVID-19 case profiles and public health and social measures and could lead to the biases in predicting ${R}_t$. Accounting for the impact of these factors, the time-varying quantification of serial interval distributions could lead to improved estimation of ${R}_t$, and provide additional insights into the impact of public health measures on transmission.

Analysis of the impact of COVID-19 variants and vaccination on the time-varying reproduction number: statistical methods.

The COVID-19 pandemic has profoundly impacted global health systems, requiring the monitoring of infection waves and strategies to control transmission. Estimating the time-varying reproduction number is crucial for understanding the epidemic and guiding interventions. Probability distributions of serial interval are estimated for Pre-Delta and Delta periods. We conducted a comparative analysis of time-varying reproduction numbers, taking into account population immunity and variant differences. We incorporated the regional heterogeneity and age distribution of the population, as well as the evolving variants and vaccination rates over time. COVID-19 transmission dynamics were analyzed with variants and vaccination. The reproduction number is computed with and without considering variant-based immunity. In addition, values of reproduction number significantly differed by variants, emphasizing immunity's importance. Enhanced vaccination efforts and stringent control measures were effective in reducing the transmission of the Delta variant. Conversely, Pre-Delta variant appeared less influenced by immunity levels, due to lower vaccination rates. Furthermore, during the Pre-Delta period, there was a significant difference between the region-specific and the non-region-specific reproduction numbers, with particularly distinct pattern differences observed in Gangwon, Gyeongbuk, and Jeju in Korea. This research elucidates the dynamics of COVID-19 transmission concerning the dominance of the Delta variant, the efficacy of vaccinations, and the influence of immunity levels. It highlights the necessity for targeted interventions and extensive vaccination coverage. This study makes a significant contribution to the understanding of disease transmission mechanisms and informs public health strategies.

Incubation Period and Serial Interval of Mpox in 2022 Global Outbreak Compared with Historical Estimates.

Understanding changes in the transmission dynamics of mpox requires comparing recent estimates of key epidemiologic parameters with historical data. We derived historical estimates for the incubation period and serial interval for mpox and contrasted them with pooled estimates from the 2022 outbreak. Our findings show the pooled mean infection-to-onset incubation period was 8.1 days for the 2022 outbreak and 8.2 days historically, indicating the incubation periods remained relatively consistent over time, despite a shift in the major mode of transmission. However, we estimated the onset-to-onset serial interval at 8.7 days using 2022 data, compared with 14.2 days using historical data. Although the reason for this shortening of the serial interval is unclear, it may be because of increased public health interventions or a shift in the mode of transmission. Recognizing such temporal shifts is essential for informed response strategies, and public health measures remain crucial for controlling mpox and similar future outbreaks.

Transmissibility of the variant of concern for SARS-CoV-2 in six regions

IntroductionDifferences in transmissibility of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants of concern (VOCs) in different districts are hard to assess. To address this, our study focused on calculating the Real-time reproduction number (Rt) for these variants in different regions. MethodsAccording to the criteria defined by the World Health Organization (WHO), the global landscape was categorized into six distinct regions. In each region, the predominant SARS-CoV-2 variant was first identified based on the proportion of variant sequencing analysis results. Then, using serial interval (SI) parameters, we calculated Rt for the relevant Variant of Concern (VOC) in each region. This approach enabled us to compare the Rt values of the same variant across different regions and analyze the transmissibility of each region's variant in relation to the overall situation in that region. ResultsThe progression of VOC for SARS-CoV-2 shows regional variations. However, a common sequence of evolution is observed: Wild-type → Alpha → Beta → Delta → Omicron. Moreover, an increasing trend is discerned within diverse regions where the shift in Rt of distinct VOC corresponds with the overarching Rt route of SARS-CoV-2 in specific regions. ConclusionAs the COVID-19 pandemic advances, regional epidemiological trends are aligning, likely due to similar virus mutations and shared public health strategies, suggesting opportunities for standardized global responses.

Retrospective estimation of the time-varying effective reproduction number for a COVID-19 outbreak in Shenyang, China: An observational study.

The time-varying effective reproduction number Re(t) is essential for designing and adjusting public health responses. Retrospective analysis of Re(t) helps to evaluate health emergency capabilities. We conducted this study to estimate the Re(t) of the Corona Virus Disease 2019 (COVID-19) outbreak caused by SARS-CoV-2 Omicron in Shenyang, China. Data on the daily incidence of this Corona Virus Disease 2019 outbreak between March 5, 2022, and April 25, 2022, in Shenyang, China, were downloaded from the Nationwide Notifiable Infectious Diseases Reporting Information System. Infector-infectee pairs were identified through epidemiological investigation. Re(t) was estimated by R-studio Package "EpiEstim" based on Bayesian framework through parameter and nonparametric method, respectively. About 1134 infections were found in this outbreak, with 20 confirmed cases and 1124 asymptomatic infections. Fifty-four infector-infectee pairs were identified and formed a serial interval list, and 15 infector-infectee pairs were included in the generation time table. Re(t) calculated by parameter and nonparametric method all peaked on March 17, 2022, with a value of 2.58 and 2.54 and decreased to <1 after March 28, 2022. There was no statistical difference in the Re(t) distribution calculated using the 2 methods (t = 0.001, P > .05). The present study indicated that the decisive response of Shenyang, China, played a significant role in preventing the spread of the epidemic, and the retrospective analysis provided novel insights into the outbreak response to future public health emergencies.

Bayesian estimation of the time-varying reproduction number for pulmonary tuberculosis in Iran: A registry-based study from 2018 to 2022 using new smear-positive cases

IntroductionTuberculosis (TB) is one of the most prevalent infectious diseases in the world, causing major public health problems in developing countries. The rate of TB incidence in Iran was estimated to be 13 per 100,000 in 2021. This study aimed to estimate the reproduction number and serial interval for pulmonary tuberculosis in Iran. Material and methodsThe present national historical cohort study was conducted from March 2018 to March 2022 based on data from the National Tuberculosis and Leprosy Registration Center of Iran's Ministry of Health and Medical Education (MOHME). The study included 30,762 tuberculosis cases and 16,165 new smear-positive pulmonary tuberculosis patients in Iran. We estimated the reproduction number of pulmonary tuberculosis in a Bayesian framework, which can incorporate uncertainty in estimating it. Statistical analyses were accomplished in R software. ResultsThe mean age at diagnosis of patients was 52.3 ± 21.2 years, and most patients were in the 35–63 age group (37.1%). Among the data, 9121 (56.4%) cases were males, and 7044 (43.6%) were females. Among patients, 7459 (46.1%) had a delayed diagnosis between 1 and 3 months. Additionally, 3039 (18.8%) cases were non-Iranians, and 2978 (98%) were Afghans. The time-varying reproduction number for pulmonary tuberculosis disease was calculated at an average of 1.06 ± 0.05 (95% Crl 0.96–1.15). ConclusionsIn this study, the incidence and the time-varying reproduction number of pulmonary tuberculosis showed the same pattern. The mean of the time-varying reproduction number indicated that each infected person is causing at least one new infection over time, and the chain of transmission is not being disrupted.

Scenarios of future mpox outbreaks among men who have sex with men: a modelling study based on cross-sectional seroprevalence data from the Netherlands, 2022.

BackgroundFollowing the 2022-2023 mpox outbreak, crucial knowledge gaps exist regarding orthopoxvirus-specific immunity in risk groups and its impact on future outbreaks.AimWe combined cross-sectional seroprevalence studies in two cities in the Netherlands with mathematical modelling to evaluate scenarios of future mpox outbreaks among men who have sex with men (MSM).MethodsSerum samples were obtained from 1,065 MSM attending Centres for Sexual Health (CSH) in Rotterdam or Amsterdam following the peak of the Dutch mpox outbreak and the introduction of vaccination. For MSM visiting the Rotterdam CSH, sera were linked to epidemiological and vaccination data. An in-house developed ELISA was used to detect vaccinia virus (VACV)-specific IgG. These observations were combined with published data on serial interval and vaccine effectiveness to inform a stochastic transmission model that estimates the risk of future mpox outbreaks.ResultsThe seroprevalence of VACV-specific antibodies was 45.4% and 47.1% in Rotterdam and Amsterdam, respectively. Transmission modelling showed that the impact of risk group vaccination on the original outbreak was likely small. However, assuming different scenarios, the number of mpox cases in a future outbreak would be markedly reduced because of vaccination. Simultaneously, the current level of immunity alone may not prevent future outbreaks. Maintaining a short time-to-diagnosis is a key component of any strategy to prevent new outbreaks.ConclusionOur findings indicate a reduced likelihood of large future mpox outbreaks among MSM in the Netherlands under current conditions, but emphasise the importance of maintaining population immunity, diagnostic capacities and disease awareness.

Detecting changes in generation and serial intervals under varying pathogen biology, contact patterns and outbreak response.

The epidemiological characteristics of SARS-CoV-2 transmission have changed over the pandemic due to emergence of new variants. A decrease in the generation or serial intervals would imply a shortened transmission timescale and, hence, outbreak response measures would need to expand at a faster rate. However, there are challenges in measuring these intervals. Alongside epidemiological changes, factors like varying delays in outbreak response, social contact patterns, dependence on the growth phase of an outbreak, and effects of exposure to multiple infectors can also influence measured generation or serial intervals. To guide real-time interpretation of variant data, we simulated concurrent changes in the aforementioned factors and estimated the statistical power to detect a change in the generation and serial interval. We compared our findings to the reported decrease or lack thereof in the generation and serial intervals of different SARS-CoV-2 variants. Our study helps to clarify contradictory outbreak observations and informs the required sample sizes under certain outbreak conditions to ensure that future studies of generation and serial intervals are adequately powered.

Parametric analysis of the transmission dynamics during indigenous aggregated outbreaks caused by five SARS-CoV-2 strains in Nanjing, China.

SARS-CoV-2 strains have been of great concern due to their high infectivity and antibody evasion. In this study, data were collected on indigenous aggregated outbreaks in Nanjing from January 2020 to December 2022, caused by five strains including the original strain, the Delta variant, and the Omicron variant (BA.2, BA.5.2, and BF.7). The basic epidemiological characteristics of infected individuals were described and then parametric analysis of transmission dynamics was performed, including the calculation of incubation period, serial interval (SI), the basic reproductive number (R0), and the household secondary attack rate (HSAR). Finally, we compared the trends of transmission dynamic parameters of different strains. The incubation period for the original strain, the Delta variant, Omicron BA.2, Omicron BA.5.2, and Omicron BF.7 were 6 d (95% CI: 3.5-7.5 d), 5 d (95% CI: 4.0-6.0 d), 3 d (95% CI: 3.0-4.0 d), 3 d (95% CI: 3.0-3.0 d), and 2 d (95% CI: 2.0-3.0 d), respectively; Also, the SI of the five strains were 5.69 d, 4.79 d, 2.7 d, 2.12 d, and 2.43 d, respectively. Notably, the incubation period and SI of the five had both a progressive shortening trend (p < 0.001); Moreover, R0 of the five were 2.39 (95% CI: 1.30-4.29), 3.73 (95% CI: 2.66-5.15), 5.28 (95% CI: 3.52-8.10), 5.54 (95% CI: 2.69-11.17), 7.39 (95% CI: 2.97-18.76), with an increasing trend gradually (p < 0.01); HSAR of the five were 25.5% (95% CI: 20.1-31.7%), 27.4% (95% CI: 22.0-33.4%), 42.9% (95% CI: 34.3-51.8%), 53.1% (95% CI: 45.0-60.9%), 41.4% (95% CI, 25.5-59.3%), also with an increasing trend (p < 0.001). Compared to the original strain, the incubation period and SI decreased while R0 and HSAR increased, suggesting that transmission in the population was faster and the scope of the population was wider. Overall, it's crucial to keep implementing comprehensive measures like monitoring and alert systems, herd immunization plans, and outbreak control.

Variability in the serial interval of COVID-19 in South Korea: a comprehensive analysis of age and regional influences.

Quantifying the transmissibility over time, particularly by region and age, using parameters such as serial interval and time-varying reproduction number, helps in formulating targeted interventions. Moreover, considering the impact of geographical factors on transmission provides valuable insights into the effectiveness of control measures. Drawing on a comprehensive dataset of COVID-19 cases in South Korea, we analyzed transmission dynamics with a focus on age and regional variations. The dataset, compiled through the efforts of dedicated epidemiologists, includes information on symptom onset dates, enabling detailed investigations. The pandemic was divided into distinct phases, aligning with changes in policies, emergence of variants, and vaccination efforts. We analyzed various interventions such as social distancing, vaccination rates, school closures, and population density. Key parameters like serial interval, heatmaps, and time-varying reproduction numbers were used to quantify age and region-specific transmission trends. Analysis of transmission pairs within age groups highlighted the significant impact of school closure policies on the spread among individuals aged 0-19. This analysis also shed light on transmission dynamics within familial and educational settings. Changes in confirmed cases over time revealed a decrease in spread among individuals aged 65 and older, attributed to higher vaccination rates. Conversely, densely populated metropolitan areas experienced an increase in confirmed cases. Examination of time-varying reproduction numbers by region uncovered heterogeneity in transmission patterns, with regions implementing strict social distancing measures showing both increased confirmed cases and delayed spread, indicating the effectiveness of these policies. Our findings underscore the importance of evaluating and tailoring epidemic control policies based on key COVID-19 parameters. The analysis of social distancing measures, school closures, and vaccine impact provides valuable insights into controlling transmission. By quantifying the impact of these interventions on different age groups and regions, we contribute to the ongoing efforts to combat the COVID-19 pandemic effectively.

Updating Reproduction Number Estimates for Mpox in the Democratic Republic of Congo Using Surveillance Data.

Incidence of human monkeypox (mpox) has been increasing in West and Central Africa, including in the Democratic Republic of Congo (DRC), where monkeypox virus (MPXV) is endemic. Most estimates of the pathogen's transmissibility in the DRC are based on data from the 1980s. Amid the global 2022 mpox outbreak, new estimates are needed to characterize the virus' epidemic potential and inform outbreak control strategies. We used the R package vimes to identify clusters of laboratory-confirmed mpox cases in Tshuapa Province, DRC. Cases with both temporal and spatial data were assigned to clusters based on the disease's serial interval and spatial kernel. We used the size of the clusters to infer the effective reproduction number, Rt, and the rate of zoonotic spillover of MPXV into the human population. Out of 1,463 confirmed mpox cases reported in Tshuapa Province between 2013 and 2017, 878 had both date of symptom onset and a location with geographic coordinates. Results include an estimated Rt of 0.82 (95% CI: 0.79-0.85) and a rate of 132 (95% CI: 122-143) spillovers per year assuming a reporting rate of 25%. This estimate of Rt is larger than most previous estimates. One potential explanation for this result is that Rt could have increased in the DRC over time owing to declining population-level immunity conferred by smallpox vaccination, which was discontinued around 1982. Rt could be overestimated if our assumption of one spillover event per cluster does not hold. Our results are consistent with increased transmissibility of MPXV in Tshuapa Province.

Temporal cross-correlation between Polar® heart rate monitor interface board and ECG to measure RR interval at rest

BACKGROUND: A Polar heart rate monitor is a device that measures RR intervals, but has not been correlated to accurately measure the series of RR interval signals between the ECG and the Polar® Heart Rate Monitor Interface (HRMI) Board at rest. OBJECTIVE: The aim of the study was to evaluate the temporal cross-correlations between the Polar® HRMI Board and an ECG to measure the series of RR intervals at rest. METHODS: The sample consisted of eighteen healthy male subjects and they were instructed to lie in the supine position at rest while breathing normally and a time window of the last 2 min was recorded to analyse RR intervals were obtained for each subject with a Polar® HRMI Board and an ECG. Cross-correlation analysis of RR interval signals between methods and reliability was expressed by Bland and Altman analysis. RESULTS: The cross-correlation was excellent, resulting in a mean of 0.98 ± 0.01 and no lag or delay between the signals. The bias was 0.03 ± 0.08 s or 8.0% for MeanRRi from Polar® HRMI Board and ECG, no significant difference. CONCLUSIONS: The Polar® HRMI Board is acceptable for assessment of serial RR intervals. The results support the reliability of the Mean RR interval compared to a resting ECG.

Transmission characteristics and inactivated vaccine effectiveness against transmission of the SARS-CoV-2 Omicron BA.2 variant in Shenzhen, China.

We conducted a retrospective cohort study to evaluate the transmission risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron BA.2 variant and the effectiveness of inactivated COVID-19 vaccine boosters in Shenzhen during a BA.2 outbreak period from 1 February to 21 April 2022. A total of 1,248 individuals were infected with the BA.2 variant, and 7,855 close contacts were carefully investigated. The risk factors for the high secondary attack rate of SARS-CoV-2 infection were household contacts [adjusted odds ratio (aOR): 1.748; 95% confidence interval (CI): 1.448, 2.110], younger individuals aged 0-17 years (aOR: 2.730; 95% CI: 2.118, 3.518), older persons aged ≥60 years (aOR: 1.342; 95% CI: 1.135, 1.588), women (aOR: 1.442; 95% CI: 1.210, 1.718), and the subjects exposed to the post-onset index cases (aOR: 8.546; 95% CI: 6.610, 11.050), respectively. Compared with the unvaccinated and partially vaccinated individuals, a relatively low risk of secondary attack was found for the individuals who received booster vaccination (aOR: 0.871; 95% CI: 0.761, 0.997). Moreover, a high transmission risk was found for the index cases aged ≥60 years (aOR: 1.359; 95% CI: 1.132, 1.632), whereas a relatively low transmission risk was observed for the index cases who received full vaccination (aOR: 0.642; 95% CI: 0.490, 0.841) and booster vaccination (aOR: 0.676; 95% CI: 0.594, 0.770). Compared with full vaccination, booster vaccination of inactivated COVID-19 vaccine showed an effectiveness of 24.0% (95% CI: 7.0%, 37.9%) against BA.2 transmission for the adults ≥18 years and 93.7% (95% CI: 72.4%, 98.6%) for the adults ≥60 years, whereas the effectiveness was 51.0% (95% CI: 21.9%, 69.3%) for the individuals of 14 days to 179 days after booster vaccination and 51.2% (95% CI: 37.5%, 61.9%) for the non-household contacts. The estimated mean values of the generation interval, serial interval, incubation period, latent period, and viral shedding period were 2.7 days, 3.2 days, 2.4 days, 2.1 days, and 17.9 days, respectively. In summary, our results confirmed that the main transmission route of Omicron BA.2 subvariant was household contact, and booster vaccination of the inactivated vaccines was relatively effective against BA.2 subvariant transmission in older people.