Factors Associated with the Outcome of 2023 Diphtheria Outbreak in Jigawa State, Nigeria: A Retrospective Review of the Surveillance Data.

OBJECTIVE: The objective of this study was to identify the factors associated with the outcome of the 2023 diphtheria outbreak in Jigawa State, Nigeria. METHODS: A descriptive cross-sectional study was conducted amongst all line-listed diphtheria cases reported from Jigawa State, Nigeria, using the 2023 Integrated Disease and Surveillance Response line list of cases that met the World Health Organization case definition of diphtheria. A total of 245 line-listed cases from January 2023 to December 2023 met the criteria for inclusion in the study. Data were analysed using IBM SPSS version 22.0 with a P value set at ≤5%. Binary logistic regression was used to identify the independent predictors of the outcome of the 2023 outbreak. RESULTS: The maximum age of the line-listed cases was 39 years, and the minimum was 1 year with a median of 8 (interquartile range = 5-8) years. More than two-thirds (68.2%) of the cases were ≥5 years of age. More than one-third of the cases (39.6%) were from the northeast senatorial zone of the state. Out of the total 245 cases, 14 died of the disease representing a case fatality rate of 6%, and an attack rate of 3.4 per 100,000 populations. The majority of the cases (95.5%) had fever, cough (81.2%), pharyngitis (86.9%), tonsillitis (96.7%) and laryngitis (82.0%). More diphtheria-related mortalities were recorded amongst cases <5 years of age (7.7%), female cases (5.9%), rural residence (7.7%) and cases from the northeast senatorial zone (8.2%) of the state. Significantly higher mortalities (8.8%, P = 0.003) were recorded amongst cases with nasopharyngitis. The odds of diphtheria-related mortality were higher amongst cases who presented clinically with nasopharyngitis and were 4 times more likely to die (adjusted odds ratio = 3.9; 95% confidence interval = 1.1-14.3) compared with those with no nasopharyngitis. CONCLUSIONS: Significantly higher mortalities were recorded amongst diphtheria cases whose samples were not taken, and those with nasopharyngitis. These findings underscored the importance of improved immunisation uptake, early and prompt case detection, investigation and proper management.

Drivers and epidemiological patterns of West Nile virus in Serbia.

Background: West Nile virus (WNV) is an emerging mosquito-borne pathogen in Serbia, where it has been detected as a cause of infection in humans since 2012. We analyzed and modelled WNV transmission patterns in the country between 2012 and 2023. Methods: We applied a previously developed modelling approach to quantify epidemiological parameters of interest and to identify the most important environmental drivers of the force of infection (FOI) by means of statistical analysis in the human population in the country. Results: During the study period, 1,387 human cases were recorded, with substantial heterogeneity across years. We found that spring temperature is of paramount importance for WNV transmission, as FOI magnitude and peak timing are positively associated with it. Furthermore, FOI is also estimated to be greater in regions with a larger fraction of older adult people, who are at higher risk to develop severe infections. Conclusion: Our results highlight that temperature plays a key role in shaping WNV outbreak magnitude in Serbia, confirming the association between spring climatic conditions and WNV human transmission risk and thus pointing out the importance of this factor as a potential early warning predictor for timely application of preventive and control measures.

Interacting particle models on the impact of spatially heterogeneous human behavioral factors on dynamics of infectious diseases.

Human behaviors have non-negligible impacts on spread of contagious disease. For instance, large-scale gathering and high mobility of population could lead to accelerated disease transmission, while public behavioral changes in response to pandemics may effectively reduce contacts and suppress the peak of the outbreak. In order to understand how spatial characteristics like population mobility and clustering interplay with epidemic outbreaks, we formulate a stochastic-statistical environment-epidemic dynamic system (SEEDS) via an agent-based biased random walk model on a two-dimensional lattice. The "popularity" and "awareness" variables are taken into consideration to capture human natural and preventive behavioral factors, which are assumed to guide and bias agent movement in a combined way. It is found that the presence of the spatial heterogeneity, like social influence locality and spatial clustering induced by self-aggregation, potentially suppresses the contacts between agents and consequently flats the epidemic curve. Surprisedly, disease responses might not necessarily reduce the susceptibility of informed individuals and even aggravate disease outbreak if each individual responds independently upon their awareness. The disease control is achieved effectively only if there are coordinated public-health interventions and public compliance to these measures. Therefore, our model may be useful for quantitative evaluations of a variety of public-health policies.

Rotavirus outbreaks in China, 1982-2021: a systematic review.

Background: Rotavirus is globally recognized as an important cause of acute gastroenteritis in young children. Whereas previous studies focused more on sporadic diarrhea, the epidemiological characteristics of rotavirus outbreaks have not been systematically understood. Methods: This systematic review was carried out according to the Preferred Reporting Items for Systematic Review and Meta-Analysis standards, WANFANG, China National Knowledge Infrastructure (CNKI), PubMed, and Web of Science databases were searched from database inception to February 20, 2022. We used SPSS 21.0 statistical software for data analysis, RStudio1.4.1717, and ArcGIS trial version for plotting bar graphs and maps. Results: Among 1,596 articles, 78 were included, with 92 rotavirus outbreaks and 96,128 cases. Most outbreaks (67.39%, 62/92) occurred in winter and spring. The number of rotavirus outbreaks reported in the eastern region was more than that in the western region. Outbreaks were most commonly reported in villages (33/92, 35.87%), followed by hospitals (19, 20.65%). The outbreak duration was longer in factories and workers' living places, and villages, while it was shorter in hospitals. Waterborne transmission was the main transmission mode, with the longest duration and the largest number of cases. Rotavirus groups were identified in 66 outbreaks, with 40 outbreaks (60.61%) caused by Group B rotaviruses and 26 outbreaks (39.39%) caused by Group A rotaviruses. Significant differences were found in duration, number of cases, settings, population distribution, and transmission modes between Groups A and B rotavirus outbreaks. Conclusion: Rotavirus is an important cause of acute gastroenteritis outbreaks in China. It should also be considered in the investigation of acute gastroenteritis outbreaks, especially norovirus-negative outbreaks.

Assessment of epidemic risk state and its change trend of public hospital in underdeveloped area in different stages.

Objective: Epidemics are sudden and rapidly spreading. Hospitals in underdeveloped areas are particularly vulnerable in case of an outbreak. This paper aims to assess the epidemic risk state and its change trend of hospitals in different epidemic stages, identify the key factors affecting hospital epidemic risk change, provide priority reference for hospital epidemic risk control, and enhance the hospital's ability to respond to sudden epidemics. Methods: Based on Grounded theory, the epidemic risk indicators that affect hospital safety are summarized. The concept of epidemic risk state and its random state space is proposed according to Markov chain theory. The impact of each indicator on the random risk state and its change is comprehensively assessed from two aspects: risk occurrence probability and risk loss. Finally, the assessment of the hospital epidemic risk state and its change at different stages is achieved. Results: The stable risk states of public hospitals in underdeveloped areas in non-epidemic stage t0, early epidemic stage t1, and outbreak stage t2 are P ^ t 0 ( S n ) = { 0 . 142 , 0 . 546 , 0 . 220 , 0 . 093 } , P ^ t 1 ( S n ) = { 0 . 025 , 0 . 364 , 0 . 254 , 0 . 357 } , and P ^ t 2 ( S n ) = { 0 . 020 , 0 . 241 , 0 . 191 , 0 . 548 } , respectively. In non-epidemic stage, the key factor in improving the hospital epidemic risk state is emergency funding. In early epidemic stage, the key factors in improving the hospital epidemic risk state are the training of medical staff in epidemic prevention skills and the management of public health. In outbreak state, the key factor in improving the hospital epidemic risk state is the training of medical staff in epidemic prevention skills and psychological awareness. Conclusion: This paper proposes the concept of epidemic risk state, providing an effective assessment method for the epidemic risk state and its change trend in public hospitals. According to the assessment, public hospitals in underdeveloped areas in different epidemic stages should adopt different risk control strategies to improve their current risk state. Blind risk control is inefficient and may even cause the epidemic risk to transition toward a more dangerous state.

The timeline of overseas imported cases acts as a strong indicator of dengue outbreak in mainland China.

The emergence of dengue viruses in new, susceptible human populations worldwide is increasingly influenced by a combination of local and global human movements and favorable environmental conditions. While various mathematical models have explored the impact of environmental factors on dengue outbreaks, the significant role of human mobility both internationally and domestically in transmitting the disease has been less frequently addressed. In this context, we introduce a modeling framework that integrates the effects of international travel-induced imported cases, climatic conditions, and local human movements to assess the spatiotemporal dynamics of dengue transmission. Utilizing the generation matrix method, we calculate the basic reproduction number and its sensitivity to various model parameters. Through numerical simulations using data on climate, human mobility, and reported dengue cases in mainland China, our model demonstrates a good agreement with observed data upon validation. Our findings reveal that while climatic conditions are a key driver for the rapid dengue transmission, human mobility plays a crucial role in its local spread. Importantly, the model highlights the significant impact of imported cases from overseas on the initiation of dengue outbreaks and their contribution to increasing the disease incidence rate by 34.6%. Furthermore, the analysis identifies that dengue cases originating from regions, such as Cambodia and Myanmar internationally, and Guangzhou and Xishuangbanna domestically, have the potential to significantly increase the disease burden in mainland China. These insights emphasize the critical need to include data on imported cases and domestic travel patterns in disease outbreak models to improve the precision of predictions, thereby enhancing dengue prevention, surveillance, and response strategies.

Quantifying the risk of spillover reduction programs for human health.

Reducing spillover of zoonotic pathogens is an appealing approach to preventing human disease and minimizing the risk of future epidemics and pandemics. Although the immediate human health benefit of reducing spillover is clear, over time, spillover reduction could lead to counterintuitive negative consequences for human health. Here, we use mathematical models and computer simulations to explore the conditions under which unanticipated consequences of spillover reduction can occur in systems where the severity of disease increases with age at infection. Our results demonstrate that, because the average age at infection increases as spillover is reduced, programs that reduce spillover can actually increase population-level disease burden if the clinical severity of infection increases sufficiently rapidly with age. If, however, immunity wanes over time and reinfection is possible, our results reveal that negative health impacts of spillover reduction become substantially less likely. When our model is parameterized using published data on Lassa virus in West Africa, it predicts that negative health outcomes are possible, but likely to be restricted to a small subset of populations where spillover is unusually intense. Together, our results suggest that adverse consequences of spillover reduction programs are unlikely but that the public health gains observed immediately after spillover reduction may fade over time as the age structure of immunity gradually re-equilibrates to a reduced force of infection.

Global prevalence of norovirus gastroenteritis after emergence of the GII.4 Sydney 2012 variant: a systematic review and meta-analysis.

Introduction: Norovirus is widely recognized as a leading cause of both sporadic cases and outbreaks of acute gastroenteritis (AGE) across all age groups. The GII.4 Sydney 2012 variant has consistently prevailed since 2012, distinguishing itself from other variants that typically circulate for a period of 2-4 years. Objective: This review aims to systematically summarize the prevalence of norovirus gastroenteritis following emergence of the GII.4 Sydney 2012 variant. Methods: Data were collected from PubMed, Embase, Web of Science, and Cochrane databases spanning the period between January 2012 and August 2022. A meta-analysis was conducted to investigate the global prevalence and distribution patterns of norovirus gastroenteritis from 2012 to 2022. Results: The global pooled prevalence of norovirus gastroenteritis was determined to be 19.04% (16.66-21.42%) based on a comprehensive analysis of 70 studies, which included a total of 85,798 sporadic cases with acute gastroenteritis and identified 15,089 positive cases for norovirus. The prevalence rate is higher in winter than other seasons, and there are great differences among countries and age groups. The pooled attack rate of norovirus infection is estimated to be 36.89% (95% CI, 36.24-37.55%), based on a sample of 6,992 individuals who tested positive for norovirus out of a total population of 17,958 individuals exposed during outbreak events. Conclusion: The global prevalence of norovirus gastroenteritis is always high, necessitating an increased emphasis on prevention and control strategies with vaccine development for this infectious disease, particularly among the children under 5 years old and the geriatric population (individuals over 60 years old).

Marked increase in cryptosporidiosis cases, Spain, 2023.

BackgroundBy mid-September 2023, several event notifications related to cryptosporidiosis had been identified from different regions in Spain. Therefore, a request for urgent notification of cryptosporidiosis cases to the National Surveillance Network was launched.AimWe aimed at assessing the extent of the increase in cases, the epidemiological characteristics and the transmission modes and compared to previous years.MethodsWe analysed data on case notifications, outbreak reports and genotypes focusing on June-October 2023 and compared the results to 2016-2022.ResultsIn 2023, 4,061 cryptosporidiosis cases were notified in Spain, which is an increase compared to 2016-2022. The cumulative incidence was 8.3 cases per 100,000 inhabitants in 2023, sixfold higher than the median of 1.4 cases per 100,000 inhabitants 2016-2022. Almost 80% of the cases were notified between June and October. The largest outbreaks were related to contaminated drinking water or swimming pools. Cryptosporidium hominis was the most common species in the characterised samples (115/122), and the C. hominis IfA12G1R5 subtype, previously unusual in Spain, was detected from 76 (62.3%) of the 122 characterised samples.ConclusionsA substantial increase in cryptosporidiosis cases was observed in 2023. Strengthening surveillance of Cryptosporidium is essential for prevention of cases, to better understand trends and subtypes circulating and the impact of adverse meteorological events.

Prevention and control of Ebola virus transmission: mathematical modelling and data fitting.

The Ebola virus disease (EVD) has been endemic since 1976, and the case fatality rate is extremely high. EVD is spread by infected animals, symptomatic individuals, dead bodies, and contaminated environment. In this paper, we formulate an EVD model with four transmission modes and a time delay describing the incubation period. Through dynamical analysis, we verify the importance of blocking the infection source of infected animals. We get the basic reproduction number without considering the infection source of infected animals. And, it is proven that the model has a globally attractive disease-free equilibrium when the basic reproduction number is less than unity; the disease eventually becomes endemic when the basic reproduction number is greater than unity. Taking the EVD epidemic in Sierra Leone in 2014-2016 as an example, we complete the data fitting by combining the effect of the media to obtain the unknown parameters, the basic reproduction number and its time-varying reproduction number. It is shown by parameter sensitivity analysis that the contact rate and the removal rate of infected group have the greatest influence on the prevalence of the disease. And, the disease-controlling thresholds of these two parameters are obtained. In addition, according to the existing vaccination strategy, only the inoculation ratio in high-risk areas is greater than 0.4, the effective reproduction number can be less than unity. And, the earlier the vaccination time, the greater the inoculation ratio, and the faster the disease can be controlled.

Epidemiological modeling of SARS-CoV-2 in white-tailed deer (Odocoileus virginianus) reveals conditions for introduction and widespread transmission.

Emerging infectious diseases with zoonotic potential often have complex socioecological dynamics and limited ecological data, requiring integration of epidemiological modeling with surveillance. Although our understanding of SARS-CoV-2 has advanced considerably since its detection in late 2019, the factors influencing its introduction and transmission in wildlife hosts, particularly white-tailed deer (Odocoileus virginianus), remain poorly understood. We use a Susceptible-Infected-Recovered-Susceptible epidemiological model to investigate the spillover risk and transmission dynamics of SARS-CoV-2 in wild and captive white-tailed deer populations across various simulated scenarios. We found that captive scenarios pose a higher risk of SARS-CoV-2 introduction from humans into deer herds and subsequent transmission among deer, compared to wild herds. However, even in wild herds, the transmission risk is often substantial enough to sustain infections. Furthermore, we demonstrate that the strength of introduction from humans influences outbreak characteristics only to a certain extent. Transmission among deer was frequently sufficient for widespread outbreaks in deer populations, regardless of the initial level of introduction. We also explore the potential for fence line interactions between captive and wild deer to elevate outbreak metrics in wild herds that have the lowest risk of introduction and sustained transmission. Our results indicate that SARS-CoV-2 could be introduced and maintained in deer herds across a range of circumstances based on testing a range of introduction and transmission risks in various captive and wild scenarios. Our approach and findings will aid One Health strategies that mitigate persistent SARS-CoV-2 outbreaks in white-tailed deer populations and potential spillback to humans.

Epidemiology of Mpox Cases, and Tecovirimat and JYNNEOS Utilization, Alameda County, California, June-October 2022.

CONTEXT: The 2022 United States mpox outbreak disproportionately affected racial and ethnic minority gay, bisexual, and other men who have sex with men. PROGRAM: We utilized surveillance data and vaccination registries to determine whether populations most impacted by mpox in Alameda County received JYNNEOS vaccines and tecovirimat (TPOXX) during June 1-October 31, 2022. IMPLEMENTATION: Alameda County Public Health Department responded to the mpox epidemic through partnerships with local health care providers who serve communities disproportionately affected by mpox. EVALUATION: During June 1-October 31, 2022, a total of 242 mpox cases were identified in Alameda County. Mpox incidence rates per 100 000 were highest among Black/African American (35.7; 95% confidence interval [CI], 26.8-46.5) and Hispanic/Latinx (25.1; CI, 20.1-30.9) residents, compared to Asian (3.8; CI, 2.3-5.9) and White (10.5; CI, 7.7-13.9) residents. Most confirmed cases were identified as gay, lesbian, or same-gender-loving (134, 67.3%) and bisexual (31, 15.6%); 226 (93.8%) cases were male. Sixty-nine (28.5%) mpox patients received TPOXX. There were no statistically significant differences in demographic and clinical characteristics of mpox cases when compared by TPOXX receipt status. JYNNEOS vaccine was received by 8277 Alameda County residents. The largest proportion of vaccinees were White residents (40.2%). Administration rates per 100 000 men who have sex with men were lowest among Asian and Hispanic/Latinx individuals, at 8779 (CI, 8283-9296) and 14 953 (CI, 14 156-15 784), respectively. Black/African American and Hispanic/Latinx males had the lowest vaccination-to-case ratios at 16.7 and 14.8, respectively. DISCUSSION: Mpox disproportionately affected Black/African American and Hispanic/Latinx men who have sex with men in Alameda County. Strong partnerships with local health care providers ensured that persons with mpox received TPOXX treatment when indicated. However, higher JYNNEOS vaccine uptake in Black and Latinx communities needs improvement through ongoing and meaningful engagement with Black/African American and Hispanic/Latinx gay, bisexual, and transgender communities.

Detecting and quantifying heterogeneity in susceptibility using contact tracing data.

The presence of heterogeneity in susceptibility, differences between hosts in their likelihood of becoming infected, can fundamentally alter disease dynamics and public health responses, for example, by changing the final epidemic size, the duration of an epidemic, and even the vaccination threshold required to achieve herd immunity. Yet, heterogeneity in susceptibility is notoriously difficult to detect and measure, especially early in an epidemic. Here we develop a method that can be used to detect and estimate heterogeneity in susceptibility given contact by using contact tracing data, which are typically collected early in the course of an outbreak. This approach provides the capability, given sufficient data, to estimate and account for the effects of this heterogeneity before they become apparent during an epidemic. It additionally provides the capability to analyze the wealth of contact tracing data available for previous epidemics and estimate heterogeneity in susceptibility for disease systems in which it has never been estimated previously. The premise of our approach is that highly susceptible individuals become infected more often than less susceptible individuals, and so individuals not infected after appearing in contact networks should be less susceptible than average. This change in susceptibility can be detected and quantified when individuals show up in a second contact network after not being infected in the first. To develop our method, we simulated contact tracing data from artificial populations with known levels of heterogeneity in susceptibility according to underlying discrete or continuous distributions of susceptibilities. We analyzed these data to determine the parameter space under which we are able to detect heterogeneity and the accuracy with which we are able to estimate it. We found that our power to detect heterogeneity increases with larger sample sizes, greater heterogeneity, and intermediate fractions of contacts becoming infected in the discrete case or greater fractions of contacts becoming infected in the continuous case. We also found that we are able to reliably estimate heterogeneity and disease dynamics. Ultimately, this means that contact tracing data alone are sufficient to detect and quantify heterogeneity in susceptibility.

Bayesian inference for the onset time and epidemiological characteristics of emerging infectious diseases.

Background: Emerging infectious diseases pose a significant threat to global public health. Timely detection and response are crucial in mitigating the spread of such epidemics. Inferring the onset time and epidemiological characteristics is vital for accelerating early interventions, but accurately predicting these parameters in the early stages remains challenging. Methods: We introduce a Bayesian inference method to fit epidemic models to time series data based on state-space modeling, employing a stochastic Susceptible-Exposed-Infectious-Removed (SEIR) model for transmission dynamics analysis. Our approach uses the particle Markov chain Monte Carlo (PMCMC) method to estimate key epidemiological parameters, including the onset time, the transmission rate, and the recovery rate. The PMCMC algorithm integrates the advantageous aspects of both MCMC and particle filtering methodologies to yield a computationally feasible and effective means of approximating the likelihood function, especially when it is computationally intractable. Results: To validate the proposed method, we conduct case studies on COVID-19 outbreaks in Wuhan, Shanghai and Nanjing, China, respectively. Using early-stage case reports, the PMCMC algorithm accurately predicted the onset time, key epidemiological parameters, and the basic reproduction number. These findings are consistent with empirical studies and the literature. Conclusion: This study presents a robust Bayesian inference method for the timely investigation of emerging infectious diseases. By accurately estimating the onset time and essential epidemiological parameters, our approach is versatile and efficient, extending its utility beyond COVID-19.

COVID-19 outbreaks in residential aged care facilities: an agent-based modeling study.

Introduction: A disproportionate number of COVID-19 deaths occur in Residential Aged Care Facilities (RACFs), where better evidence is needed to target COVID-19 interventions to prevent mortality. This study used an agent-based model to assess the role of community prevalence, vaccination strategies, and non-pharmaceutical interventions (NPIs) on COVID-19 outcomes in RACFs in Victoria, Australia. Methods: The model simulated outbreaks in RACFs over time, and was calibrated to distributions for outbreak size, outbreak duration, and case fatality rate in Victorian RACFs over 2022. The number of incursions to RACFs per day were estimated to fit total deaths and diagnoses over time and community prevalence.Total infections, diagnoses, and deaths in RACFs were estimated over July 2023-June 2024 under scenarios of different: community epidemic wave assumptions (magnitude and frequency); RACF vaccination strategies (6-monthly, 12-monthly, no further vaccines); additional non-pharmaceutical interventions (10, 25, 50% efficacy); and reduction in incursions (30% or 60%). Results: Total RACF outcomes were proportional to cumulative community infections and incursion rates, suggesting potential for strategic visitation/staff policies or community-based interventions to reduce deaths. Recency of vaccination when epidemic waves occurred was critical; compared with 6-monthly boosters, 12-monthly boosters had approximately 1.2 times more deaths and no further boosters had approximately 1.6 times more deaths over July 2023-June 2024. Additional NPIs, even with only 10-25% efficacy, could lead to a 13-31% reduction in deaths in RACFs. Conclusion: Future community epidemic wave patterns are unknown but will be major drivers of outcomes in RACFs. Maintaining high coverage of recent vaccination, minimizing incursions, and increasing NPIs can have a major impact on cumulative infections and deaths.

Outbreak of Legionnaires' disease in Rzeszów in 2023. / Ognisko choroby legionistów w Rzeszowie w 2023 roku.

BACKGROUND: Legionnaires' disease is a type of severe pneumonia caused by Legionella bacteria. The case fatality rate in this disease is 5-10%. People with various comorbidities, smokers and the elderly are at greater risk of developing the disease. OBJECTIVE: The aim of the work is to present the results of an epidemiological investigation into the outbreak of Legionnaires' disease that occurred in the city of Rzeszów and the surrounding area in August and September 2023 and to present the threat related to the presence of Legionella bacteria in water supply installations and networks. MATERIAL AND METHODS: The material for this publication was data from an epidemiological investigation conducted in the outbreak of Legionnaires disease in Rzeszów in 2023. RESULTS: Epidemiological investigation revealed 165 cases of Legionnaires' disease in the outbreak, including 152 confirmed cases and 13 probable cases. The case fatality rate in a legionellosis outbreak was 15%. Environmental tests were carried out in residential and public buildings and industrial installations during the investigation. As part of environmental tests, 187 water samples were collected, including 87 warm water samples. CONCLUSIONS: The outbreak of Legionnaires' disease in the city of Rzeszów draws attention to the potential threat from the Legionella bacteria to the health and life of especially elderly people suffering from chronic diseases. The environmental tests carried out confirmed the highest number of Legionella bacteria at medium and high levels in water samples taken in the private apartments of sick people. Despite the lack of strict legal regulations clearly specifying the obligations regarding periodic disinfection of internal hot water supply installations, cooperation with their owners should be undertaken to enforce plans and actions in this area.

Measures for preventing norovirus outbreaks on campus in economically underdeveloped areas and countries: evidence from rural areas in Western China.

Background: The outbreak of norovirus represents a significant public health emergency within densely populated, impoverished, and underdeveloped areas and countries. Our objective is to conduct an epidemiology study of a norovirus outbreak that occurred in a kindergarten located in rural western China. We aim to raise awareness and garner increased attention towards the prevention and control of norovirus, particularly in economically underdeveloped regions. Methods: Retrospective on-site epidemiological investigation results, including data on school layout, case symptoms, onset time, disposal methods and sample testing results, questionnaire surveys, and case-control study were conducted in a kindergarten to analyze the underlying causes of the norovirus outbreak. Results: A total of 15 cases were identified, with an attack rate of 44.12% (15/34). Among them, 10 cases were diagnosed through laboratory tests, and 5 cases were diagnosed clinically. Vomiting (100%, 15/15) and diarrhea (93.33%, 14/15) were the most common symptoms in the outbreak. Case control study revealed that cases who had close contact (<1 m) with the patient's vomitus (OR = 5.500) and those who had close contact with similar patients (OR = 8.000) had significantly higher ORs compared to the control participants. The current study demonstrated that improper handling of vomitus is positively associated with norovirus outbreak. The absence of standardized disinfection protocols heightens the risk of norovirus outbreaks. Conclusion: To our knowledge, this study represents the first investigation into a norovirus outbreak in rural areas of western China. We aspire that amidst rapid economic development, a greater emphasis will be placed on the prevention and control of infectious diseases in economically underdeveloped areas and countries.

Measles outbreak investigation in Berhet District, North Shewa, Ethiopia.

Introduction: Measles, though usually self-limiting, can have severe consequences influenced by factors such as vaccination and nutrition, notably vitamin A deficiency and malnutrition. Despite progress, contextual changes and implementation issues have hampered efforts, resulting in increased outbreaks and cases of measles. This study seeks to pinpoint outbreak features, risk factors, and strategies for preventing and controlling measles. Methods: A descriptive cross-sectional study and a 1:2 unmatched case-control study design were employed. All 101 suspected measles cases listed on the line-list were included in the descriptive research, with 60 measles patients and 120 controls included in the case-control investigation. Line-list data were cleaned and analyzed using a pivot table in Microsoft Excel 2016. Subsequently, the data were cleaned, entered into Epi Info 7.2, and exported to SPSS 26 for analysis. Results: Twenty cases occurred per 10,000 individuals. Men accounted for 67.3% of cases, with ages ranging from 5 months to 45 years and mean and standard deviations of 9.6 and 7.6, respectively. Age group of 5-14 years comprised 57.4% of cases, followed by 1-4 years with 24.8%. Being unvaccinated against measles showed an adjusted odds ratio (AOR) of 12.06 (95% CI: 3.12-46.52). Travel history to regions with active cases had an AOR of 5.73 (95% CI: 1.78-18.38). Contact with a measles patient showed an AOR of 10.3 (95% CI: 3.48-30.5). Understanding the measles transmission mechanism had an AOR of 0.164 (95% CI: 0.049-0.55), and awareness of the disease's preventability had an AOR of 0.233 (95% CI: 0.67-0.811). All factors were independently associated with the illness. Conclusion: This outbreak affected a broader age range with a high attack rate, mainly in the age group of 5-14-years. Over 35% of cases lacked measles vaccination, indicating low administrative vaccine coverage. Factors contributing to the outbreak include lack of measles vaccination, travel to areas with active disease, contact with cases, and insufficient knowledge of measles transmission and prevention strategies among mothers and caregivers.