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.

Reconstruction and analysis of the transmission network of African swine fever in People's Republic of China, August 2018-September 2019.

Introduction of African swine fever (ASF) to China in mid-2018 and the subsequent transboundary spread across Asia devastated regional swine production, affecting live pig and pork product-related markets worldwide. To explore the spatiotemporal spread of ASF in China, we reconstructed possible ASF transmission networks using nearest neighbour, exponential function, equal probability, and spatiotemporal case-distribution algorithms. From these networks, we estimated the reproduction numbers, serial intervals, and transmission distances of the outbreak. The mean serial interval between paired units was around 29 days for all algorithms, while the mean transmission distance ranged 332 -456 km. The reproduction numbers for each algorithm peaked during the first two weeks and steadily declined through the end of 2018 before hovering around the epidemic threshold value of 1 with sporadic increases during 2019. These results suggest that 1) swine husbandry practices and production systems that lend themselves to long-range transmission drove ASF spread; 2) outbreaks went undetected by the surveillance system. Efforts by China and other affected countries to control ASF within their jurisdictions may be aided by the reconstructed spatiotemporal model. Continued support for strict implementation of biosecurity standards and improvements to ASF surveillance is essential for halting transmission in China and spread across Asia.

Transmission Dynamics and Effectiveness of Control Measures during COVID-19 Surge, Taiwan, April-August 2021.

An unprecedented surge of COVID-19 cases in Taiwan in May 2021 led the government to implement strict nationwide control measures beginning May 15. During the surge, the government was able to bring the epidemic under control without a complete lockdown despite the cumulative case count reaching >14,400 and >780 deaths. We investigated the effectiveness of the public health and social measures instituted by the Taiwan government by quantifying the change in the effective reproduction number, which is a summary measure of the ability of the pathogen to spread through the population. The control measures that were instituted reduced the effective reproduction number from 2.0-3.3 to 0.6-0.7. This decrease was correlated with changes in mobility patterns in Taiwan, demonstrating that public compliance, active case finding, and contact tracing were effective measures in preventing further spread of the disease.

Acute Flaccid Myelitis Among Children - Washington, September-November 2016.

In October 2016, Seattle Children's Hospital notified the Washington State Department of Health (DOH) and CDC of a cluster of acute onset of limb weakness in children aged ≤14 years. All patients had distinctive spinal lesions largely restricted to gray matter detected by magnetic resonance imaging (MRI), consistent with acute flaccid myelitis (AFM). On November 3, DOH issued a health advisory to local health jurisdictions requesting that health care providers report similar cases. By January 24, 2017, DOH and CDC had confirmed 10 cases of AFM and excluded two suspected cases among residents of Washington during September-November 2016. Upper respiratory tract, stool, rectal, serum, buccal, and cerebrospinal fluid (CSF) specimens were tested for multiple pathogens. Hypothesis-generating interviews were conducted with patients or their parents to determine commonalities between cases. No common etiology or source of exposure was identified. Polymerase chain reaction (PCR) testing detected enterovirus D68 (EV-D68) in nasopharyngeal swabs of two patients, one of whom also tested positive for adenovirus by PCR, and detected enterovirus A71 (EV-A71) in the stool of a third patient. Mycoplasma spp. immunoglobulin M (IgM) titer was elevated in two patients, but both had upper respiratory swabs that tested negative for Mycoplasma spp. by PCR. Clinicians should maintain vigilance for AFM and report cases as soon as possible to state or local health departments.

Effectiveness of a Scaled-Up Arthritis Self-Management Program in Oregon: Walk With Ease.

OBJECTIVES: To evaluate the effectiveness of Walk With Ease (WWE), an evidence-based arthritis self-management program that was scaled up in Oregon in 2012 to 2014. METHODS: Guided by the RE-AIM (Reach, Effectiveness, Adoption, Implementation, Maintenance) framework, we collected participant surveys and attendance records and conducted observations. Preprogram and postprogram, participants self-reported pain and fatigue (scale: 0-10 points; high scores indicate more pain and fatigue) and estimated episodes of physical activity per week in the last month. RESULTS: Recruitment successfully reached the targeted population-sedentary adults with arthritis (n = 598). Participants reported significant reduction in pain (-0.47 points; P = .006) and fatigue (-0.58 points; P = .021) and increased physical activity (0.86 days/week; P < .001). WWE was adopted by workplaces and medical, community, faith, and retirement centers. Most WWE programs were delivered with high fidelity; average attendance was 47%. CONCLUSIONS: WWE is suitable for implementation by diverse organizations. Effect sizes for pain and fatigue were less than those in the original WWE studies, but this is to be expected for a large-scale implementation. Public Health Implications. WWE can be effectively translated to diverse, real-world contexts to help sedentary adults increase physical activity and reduce pain and fatigue.

Notes from the Field: Outbreak of Multidrug-Resistant Salmonella Infections Linked to Pork--Washington, 2015.

During June-July 2015, Public Health-Seattle & King County (PHSKC) and Washington State Department of Health (WADOH) investigated 22 clusters of Salmonella serotype I 4,[5], 12:i:- infections. Serotype I 4,[5], 12:i:- is the fifth most frequently reported Salmonella serotype in the United States, but is uncommon in Washington. On July 29, 2015, WADOH and PHSKC requested assistance from CDC to identify the infection source, determine risk factors, and make recommendations for prevention.

Correlation between times to SARS-CoV-2 symptom onset and secondary transmission undermines epidemic control efforts.

Severe acute respiratory coronavirus 2 (SARS-CoV-2) infections have been associated with substantial presymptomatic transmission, which occurs when the generation interval-the time between infection of an individual with a pathogen and transmission of the pathogen to another individual-is shorter than the incubation period-the time between infection and symptom onset. We collected a dataset of 257 SARS-CoV-2 transmission pairs in Japan during 2020 and jointly estimated the mean incubation period of infectors (4.8 days, 95 % CrI: 4.4-5.1 days), mean generation interval to when they infect others (4.3 days, 95 % credible interval [CrI]: 4.0-4.7 days), and the correlation (Kendall's tau: 0.5, 95 % CrI: 0.4-0.6) between these two epidemiological parameters. Our finding of a positive correlation and mean generation interval shorter than the mean infector incubation period indicates ample infectiousness before symptom onset and suggests that reliance on isolation of symptomatic COVID-19 cases as a focal point of control efforts is insufficient to address the challenges posed by SARS-CoV-2 transmission dynamics.

Age dependence of the natural history of infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): an analysis of Diamond Princess data.

BACKGROUND: Following an outbreak of coronavirus disease 2019 (COVID-19) on the cruise ship Diamond Princess, passengers and crew were followed-up to determine prognosis. This study examined the epidemiological determinants of COVID-19 natural history using these follow-up data. METHODS: Infection status, diagnosis, clinical symptoms and prognosis were analysed for all passengers and crew members on the Diamond Princess. In addition, the risk of infection associated with exposure within cabin rooms, as well as the risks of various clinical manifestations of disease, along with their epidemiological determinants, were analysed. RESULTS: The adjusted odds ratio (aOR) of infection for individuals tested by polymerase chain reaction on or after 12 February 2020 compared with individuals tested before this date was 0.53 [95% confidence interval (CI) 0.39-0.72], reflecting decreased transmission during onboard quarantine. Among infected individuals, older age was associated with elevated odds of symptomatic illness (aOR 1.01, 95% CI 1.00-1.02), severe disease (aOR 1.08, 95% CI 1.05-1.12) and death (aOR 1.12, 95% CI 1.05-1.21). CONCLUSIONS: Severe COVID-19 disease, death and symptomatic illness were more frequent among older individuals on the Diamond Princess. Older elderly cases (age ≥80 years) had the highest risks of severe disease and death. Inter-room transmission was prevented successfully by the onboard quarantine.

Assessing Public Health and Social Measures Against COVID-19 in Japan From March to June 2021.

Background: Public health and social measures (PHSM) against COVID-19 in Japan involve requesting the public to voluntarily reduce social contact; these measures are not legally binding. The effectiveness of such PHSM has been questioned with emergence of the SARS-CoV-2 Alpha variant (B.1.1.7), which exhibited elevated transmissibility. Materials and Methods: We investigated the epidemic dynamics during the fourth epidemic wave in Japan from March to June 2021 involving pre-emergency measures and declaration of a state of emergency (SoE). We estimated the effective reproduction number (R t ) before and after these interventions, and then analyzed the relationship between lower R t values and each PHSM. Results: With implementation of pre-emergency measures (PEM) in 16 prefectures, the R t was estimated to be < 1 in six prefectures; its average relative reduction ranged from 2 to 19%. During the SoE, 8 of 10 prefectures had an estimated R t < 1, and the average relative reduction was 26%-39%. No single intervention was identified that uniquely resulted in an R t value < 1. Conclusion: An SoE can substantially reduce the R t and may be required to curb a surge in cases caused by future SARS-CoV-2 variants of concern with elevated transmissibility. More customized interventions did not reduce the R t value to < 1 in this study, but that may be partly attributable to the greater transmissibility of the Alpha variant.

Phenomenological and mechanistic models for predicting early transmission data of COVID-19.

Forecasting future epidemics helps inform policy decisions regarding interventions. During the early coronavirus disease 2019 epidemic period in January-February 2020, limited information was available, and it was too challenging to build detailed mechanistic models reflecting population behavior. This study compared the performance of phenomenological and mechanistic models for forecasting epidemics. For the former, we employed the Richards model and the approximate solution of the susceptible-infected-recovered (SIR) model. For the latter, we examined the exponential growth (with lockdown) model and SIR model with lockdown. The phenomenological models yielded higher root mean square error (RMSE) values than the mechanistic models. When using the numbers from reported data for February 1 and 5, the Richards model had the highest RMSE, whereas when using the February 9 data, the SIR approximation model was the highest. The exponential model with a lockdown effect had the lowest RMSE, except when using the February 9 data. Once interventions or other factors that influence transmission patterns are identified, they should be additionally taken into account to improve forecasting.

Not all fun and games: Potential incidence of SARS-CoV-2 infections during the Tokyo 2020 Olympic Games.

The Tokyo 2020 Olympic and Paralympic Games represent the most diverse international mass gathering event held since the start of the coronavirus disease 2019 (COVID-19) pandemic. Postponed to summer 2021, the rescheduled Games were set to be held amidst what would become the highest-ever levels of COVID-19 transmission in the host city of Tokyo. At the same time, the Delta variant of concern was gaining traction as the dominant viral strain and Japan had yet to exceed fifteen percent of its population fully vaccinated against COVID-19. To quantify the potential number of secondary cases that might arise during the Olympic Games, we performed a scenario analysis using a multitype branching process model. We considered the different contributions to transmission of Games accredited individuals, the general Tokyo population, and domestic spectators. In doing so, we demonstrate how transmission might evolve in these different groups over time, cautioning against any loosening of infection prevention protocols and supporting the decision to ban all spectators. If prevention measures were well observed, we estimated that the number of new cases among Games accredited individuals would approach zero by the end of the Games. However, if transmission was not controlled our model indicated hundreds of Games accredited individuals would become infected and daily incidence in Tokyo would reach upwards of 4,000 cases. Had domestic spectators been allowed (at 50% venue capacity), we estimated that over 250 spectators might have arrived infected to Tokyo venues, potentially generating more than 300 additional secondary infections while in Tokyo/at the Games. We also found the number of cases with infection directly attributable to hypothetical exposure during the Games was highly sensitive to the local epidemic dynamics. Therefore, reducing and maintaining transmission levels below epidemic levels using public health measures would be necessary to prevent cross-group transmission.

Localized end-of-outbreak determination for coronavirus disease 2019 (COVID-19): examples from clusters in Japan.

OBJECTIVES: End-of-outbreak declarations are an important component of outbreak response because they indicate that public health and social interventions may be relaxed or lapsed. Our study aimed to assess end-of-outbreak probabilities for clusters of coronavirus disease 2019 (COVID-19) cases detected during the first wave of the COVID-19 pandemic in Japan. METHODS: A statistical model for end-of-outbreak determination, which accounted for reporting delays for new cases, was computed. Four clusters, representing different social contexts and time points during the first wave of the epidemic, were selected and their end-of-outbreak probabilities were evaluated. RESULTS: The speed of end-of-outbreak determination was most closely tied to outbreak size. Notably, accounting underascertainment of cases led to later end-of-outbreak determinations. In addition, end-of-outbreak determination was closely related to estimates of case dispersionk and the effective reproduction number Re. Increasing local transmission (Re>1) leads to greater uncertainty in the probability estimates. CONCLUSIONS: When public health measures are effective, lowerRe (less transmission on average) and larger k (lower risk of superspreading) will be in effect, and end-of-outbreak determinations can be declared with greater confidence. The application of end-of-outbreak probabilities can help distinguish between local extinction and low levels of transmission, and communicating these end-of-outbreak probabilities can help inform public health decision making with regard to the appropriate use of resources.

Estimation of the Actual Incidence of Coronavirus Disease (COVID-19) in Emergent Hotspots: The Example of Hokkaido, Japan during February-March 2020.

Following the first report of the coronavirus disease 2019 (COVID-19) in Sapporo city, Hokkaido Prefecture, Japan, on 14 February 2020, a surge of cases was observed in Hokkaido during February and March. As of 6 March, 90 cases were diagnosed in Hokkaido. Unfortunately, many infected persons may not have been recognized due to having mild or no symptoms during the initial months of the outbreak. We therefore aimed to predict the actual number of COVID-19 cases in (i) Hokkaido Prefecture and (ii) Sapporo city using data on cases diagnosed outside these areas. Two statistical frameworks involving a balance equation and an extrapolated linear regression model with a negative binomial link were used for deriving both estimates, respectively. The estimated cumulative incidence in Hokkaido as of 27 February was 2,297 cases (95% confidence interval (CI): 382-7091) based on data on travelers outbound from Hokkaido. The cumulative incidence in Sapporo city as of 28 February was estimated at 2233 cases (95% CI: 0-4893) based on the count of confirmed cases within Hokkaido. Both approaches resulted in similar estimates, indicating a higher incidence of infections in Hokkaido than were detected by the surveillance system. This quantification of the gap between detected and estimated cases helped to inform the public health response at the beginning of the pandemic and provided insight into the possible scope of undetected transmission for future assessments.

Serial interval of novel coronavirus (COVID-19) infections.

OBJECTIVE: To estimate the serial interval of novel coronavirus (COVID-19) from information on 28 infector-infectee pairs. METHODS: We collected dates of illness onset for primary cases (infectors) and secondary cases (infectees) from published research articles and case investigation reports. We subjectively ranked the credibility of the data and performed analyses on both the full dataset (n = 28) and a subset of pairs with highest certainty in reporting (n = 18). In addition, we adjust for right truncation of the data as the epidemic is still in its growth phase. RESULTS: Accounting for right truncation and analyzing all pairs, we estimated the median serial interval at 4.0 days (95% credible interval [CrI]: 3.1, 4.9). Limiting our data to only the most certain pairs, the median serial interval was estimated at 4.6 days (95% CrI: 3.5, 5.9). CONCLUSIONS: The serial interval of COVID-19 is close to or shorter than its median incubation period. This suggests that a substantial proportion of secondary transmission may occur prior to illness onset. The COVID-19 serial interval is also shorter than the serial interval of severe acute respiratory syndrome (SARS), indicating that calculations made using the SARS serial interval may introduce bias.

Initial Cluster of Novel Coronavirus (2019-nCoV) Infections in Wuhan, China Is Consistent with Substantial Human-to-Human Transmission.

Reanalysis of the epidemic curve from the initial cluster of cases with novel coronavirus (2019-nCoV) in December 2019 indicates substantial human-to-human transmission. It is possible that the common exposure history at a seafood market in Wuhan originated from the human-to-human transmission events within the market, and the early, strong emphasis that market exposure indicated animal-to-human transmission was potentially the result of observer bias. To support the hypothesis of zoonotic origin of 2019-nCoV stemming from the Huanan seafood market, the index case should have had exposure history related to the market and the virus should have been identified from animals sold at the market. As these requirements remain unmet, zoonotic spillover at the market must not be overemphasized.

Mortality Rate and Causes of Death Among Refugees Resettled in Washington State, 2006-2016.

Cause of death among refugees resettled in the United States is not well documented. This evaluation determined cause of death among refugees who resettled to and died in Washington State. Records of refugees who arrived in Washington State from 2006 to 2016 were linked to state death records for the same period. Rates and proportions of death were calculated and compared to those for all Washingtonians. From 2006 to 2016, 171 of 30,243 refugees (0.6%) resettled to and died in Washington. The age-adjusted all-cause mortality rate was 3.93 (95% CI 3.12-4.75) per 1000 refugees, compared to 6.98 (95% CI 6.96-7.00) per 1000 Washingtonians. Malignant neoplasms and heart disease were the leading causes of death for both refugees and Washingtonians. Determining cause of death among refugee populations can identify emerging trends in mortality. This information can be used to help inform disease and injury prevention interventions for refugee communities.

Epidemiological Identification of A Novel Pathogen in Real Time: Analysis of the Atypical Pneumonia Outbreak in Wuhan, China, 2019-2020.

Virological tests have now shown conclusively that a novel coronavirus is causing the 2019-2020 atypical pneumonia outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing. Characteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of eleven pathogens that have previously caused cases of atypical pneumonia. The probability that the current outbreak is due to "Disease X" (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued. The probability (expressed as a percentage) that Disease X is driving the outbreak was assessed as over 29% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 January 2020, the inferred probability of Disease X was over 49%. We showed quantitatively that the emerging outbreak of atypical pneumonia cases is consistent with causation by a novel pathogen. The proposed approach, which uses only routinely observed non-virological data, can aid ongoing risk assessments in advance of virological test results becoming available.

The Extent of Transmission of Novel Coronavirus in Wuhan, China, 2020.

A cluster of pneumonia cases linked to a novel coronavirus (2019-nCoV) was reported by China in late December 2019. Reported case incidence has now reached the hundreds, but this is likely an underestimate. As of 24 January 2020, with reports of thirteen exportation events, we estimate the cumulative incidence in China at 5502 cases (95% confidence interval: 3027, 9057). The most plausible number of infections is in the order of thousands, rather than hundreds, and there is a strong indication that untraced exposures other than the one in the epidemiologically linked seafood market in Wuhan have occurred.

Real-Time Estimation of the Risk of Death from Novel Coronavirus (COVID-19) Infection: Inference Using Exported Cases.

The exported cases of 2019 novel coronavirus (COVID-19) infection that were confirmed outside China provide an opportunity to estimate the cumulative incidence and confirmed case fatality risk (cCFR) in mainland China. Knowledge of the cCFR is critical to characterize the severity and understand the pandemic potential of COVID-19 in the early stage of the epidemic. Using the exponential growth rate of the incidence, the present study statistically estimated the cCFR and the basic reproduction number-the average number of secondary cases generated by a single primary case in a naïve population. We modeled epidemic growth either from a single index case with illness onset on 8 December, 2019 (Scenario 1), or using the growth rate fitted along with the other parameters (Scenario 2) based on data from 20 exported cases reported by 24 January 2020. The cumulative incidence in China by 24 January was estimated at 6924 cases (95% confidence interval [CI]: 4885, 9211) and 19,289 cases (95% CI: 10,901, 30,158), respectively. The latest estimated values of the cCFR were 5.3% (95% CI: 3.5%, 7.5%) for Scenario 1 and 8.4% (95% CI: 5.3%, 12.3%) for Scenario 2. The basic reproduction number was estimated to be 2.1 (95% CI: 2.0, 2.2) and 3.2 (95% CI: 2.7, 3.7) for Scenarios 1 and 2, respectively. Based on these results, we argued that the current COVID-19 epidemic has a substantial potential for causing a pandemic. The proposed approach provides insights in early risk assessment using publicly available data.

Incubation Period and Other Epidemiological Characteristics of 2019 Novel Coronavirus Infections with Right Truncation: A Statistical Analysis of Publicly Available Case Data.

The geographic spread of 2019 novel coronavirus (COVID-19) infections from the epicenter of Wuhan, China, has provided an opportunity to study the natural history of the recently emerged virus. Using publicly available event-date data from the ongoing epidemic, the present study investigated the incubation period and other time intervals that govern the epidemiological dynamics of COVID-19 infections. Our results show that the incubation period falls within the range of 2-14 days with 95% confidence and has a mean of around 5 days when approximated using the best-fit lognormal distribution. The mean time from illness onset to hospital admission (for treatment and/or isolation) was estimated at 3-4 days without truncation and at 5-9 days when right truncated. Based on the 95th percentile estimate of the incubation period, we recommend that the length of quarantine should be at least 14 days. The median time delay of 13 days from illness onset to death (17 days with right truncation) should be considered when estimating the COVID-19 case fatality risk.