Timely case notifications following the introduction of an uncommon pathogen, such as mpox, are critical for understanding disease transmission and for developing and implementing effective mitigation strategies. When Massachusetts public health officials notified the Centers for Disease Control and Prevention (CDC) about a confirmed orthopoxvirus case on May 17, 2023, which was later confirmed as mpox at CDC, mpox was not a nationally notifiable disease. Because existing processes for new data collections through the National Notifiable Disease Surveillance System were not well suited for implementation during emergency responses at the time of the mpox outbreak, several interim notification approaches were established to capture case data. These interim approaches were successful in generating daily case counts, monitoring disease transmission, and identifying high-risk populations. However, the approaches also required several data collection approvals by the federal government and the Council for State and Territorial Epidemiologists, the use of four different case report forms, and the establishment of complex data management and validation processes involving data element mapping and record-level de-duplication steps. We summarize lessons learned from these interim approaches to inform and improve case notifications during future outbreaks. These lessons reinforce CDC's Data Modernization Initiative to work in close collaboration with state, territorial, and local public health departments to strengthen case-based surveillance prior to the next public health emergency.

CaliciNet China, a network of provincial, county, and city laboratories coordinated by the Chinese Centers for Disease Control and Prevention, was launched in October 2016 to monitor the epidemiology and genotype distribution of norovirus outbreaks in China. During October 2016-September 2018, a total of 556 norovirus outbreaks were reported, and positive fecal samples from 470 (84.5%) outbreaks were genotyped. Most of these outbreaks were associated with person-to-person transmission (95.1%), occurred in childcare centers or schools (78.2%), and were reported during November-March of each year (63.5%). During the 2-year study period, 81.2% of all norovirus outbreaks were typed as GII.2[P16]. In China, most norovirus outbreaks are reported by childcare centers or schools; GII.2[P16] is the predominant genotype. Ongoing surveillance by CaliciNet China will provide information about the evolving norovirus genotype distribution and outbreak characteristics important for the development of effective interventions, including vaccines.

BACKGROUND: Southern China is at risk for arborvirus disease transmission, including Zika virus and dengue. Patients often present to clinical care with non-specific acute febrile illnesses (AFI). To better describe the etiology of AFI, we implemented a two-year AFI surveillance project at five sentinel hospitals in Yunnan and Guangdong Provinces. METHODS: Between June 2017 and August 2019, we enrolled patients between 2 and 65 years of age presenting at one sentinel hospital in Mengla County, Yunnan, and four in Jiangmen City, Guangdong, with symptoms of AFI (acute onset of fever ≥ 37.5°C within the past 7 days) without respiratory symptoms or diarrhea. Demographic, epidemiologic, and clinical information was obtained and entered into a web-based AFI surveillance database. A custom TaqMan Array card (TAC) was used to test patients' whole blood specimens for 27 different pathogens using real-time polymerase chain reaction assays. RESULTS: During the two-year project period, 836 patients were enrolled; 443 patients from Mengla County and 393 patients from Jiangmen City. The median age was 33 years [range: 2-65], and most were hospitalized [641, 77%]. Of 796 patients with valid TAC results, 341 (43%) were positive for at least one of the 10 unique pathogens detected. This included 205 (26%) patients positive for dengue virus, 60 (8%) for Orientia tsutsugamushi, and 42 (5%) for Coxiella burnetii. Ten patients (1%) in Jiangmen City tested positive for malaria, 8 of whom reported recent travel outside of China. TAC results were negative for 455 (57%) patients. None of the patients had a positive TAC detection for Zika virus. CONCLUSIONS: The project detected variability in the etiology of AFI in Southern China and highlighted the importance of differential diagnosis. Dengue, O. tsutsugamushi, and C. burnetii were the most frequently identified pathogens among enrolled AFI patients. As a non-notifiable disease, the frequent detection of C. burnetii is noteworthy and warrants additional investigation. The project provided a framework for routine surveillance for persons presenting with AFI.

The B.1.1.529 (Omicron) variant of SARS-CoV-2, the virus that causes COVID-19, was first clinically identified in the United States on December 1, 2021, and spread rapidly. By late December, it became the predominant strain, and by January 15, 2022, it represented 99.5% of sequenced specimens in the United States* (1). The Omicron variant has been shown to be more transmissible and less virulent than previously circulating variants (2,3). To better understand the severity of disease and health care utilization associated with the emergence of the Omicron variant in the United States, CDC examined data from three surveillance systems and a large health care database to assess multiple indicators across three high-COVID-19 transmission periods: December 1, 2020-February 28, 2021 (winter 2020-21); July 15-October 31, 2021 (SARS-CoV-2 B.1.617.2 [Delta] predominance); and December 19, 2021-January 15, 2022 (Omicron predominance). The highest daily 7-day moving average to date of cases (798,976 daily cases during January 9-15, 2022), emergency department (ED) visits (48,238), and admissions (21,586) were reported during the Omicron period, however, the highest daily 7-day moving average of deaths (1,854) was lower than during previous periods. During the Omicron period, a maximum of 20.6% of staffed inpatient beds were in use for COVID-19 patients, 3.4 and 7.2 percentage points higher than during the winter 2020-21 and Delta periods, respectively. However, intensive care unit (ICU) bed use did not increase to the same degree: 30.4% of staffed ICU beds were in use for COVID-19 patients during the Omicron period, 0.5 percentage points lower than during the winter 2020-21 period and 1.2 percentage points higher than during the Delta period. The ratio of peak ED visits to cases (event-to-case ratios) (87 per 1,000 cases), hospital admissions (27 per 1,000 cases), and deaths (nine per 1,000 cases [lagged by 3 weeks]) during the Omicron period were lower than those observed during the winter 2020-21 (92, 68, and 16 respectively) and Delta (167, 78, and 13, respectively) periods. Further, among hospitalized COVID-19 patients from 199 U.S. hospitals, the mean length of stay and percentages who were admitted to an ICU, received invasive mechanical ventilation (IMV), and died while in the hospital were lower during the Omicron period than during previous periods. COVID-19 disease severity appears to be lower during the Omicron period than during previous periods of high transmission, likely related to higher vaccination coverage,(†) which reduces disease severity (4), lower virulence of the Omicron variant (3,5,6), and infection-acquired immunity (3,7). Although disease severity appears lower with the Omicron variant, the high volume of ED visits and hospitalizations can strain local health care systems in the United States, and the average daily number of deaths remains substantial.(§) This underscores the importance of national emergency preparedness, specifically, hospital surge capacity and the ability to adequately staff local health care systems. In addition, being up to date on vaccination and following other recommended prevention strategies are critical to preventing infections, severe illness, or death from COVID-19.

BACKGROUND: China is vulnerable to zoonotic disease transmission due to a large agricultural work force, sizable domestic livestock population, and a highly biodiverse ecology. To better address this threat, representatives from the human, animal, and environmental health sectors in China held a One Health Zoonotic Disease Prioritization (OHZDP) workshop in May 2019 to develop a list of priority zoonotic diseases for multisectoral, One Health collaboration. METHODS: Representatives used the OHZDP Process, developed by the US Centers for Disease Control and Prevention (US CDC), to prioritize zoonotic diseases for China. Representatives defined the criteria used for prioritization and determined questions and weights for each individual criterion. A review of English and Chinese literature was conducted prior to the workshop to collect disease specific information on prevalence, morbidity, mortality, and Disability-Adjusted Life Years (DALYs) from China and the Western Pacific Region for zoonotic diseases considered for prioritization. RESULTS: Thirty zoonotic diseases were evaluated for prioritization. Criteria selected included: 1) disease hazard/severity (case fatality rate) in humans, 2) epidemic scale and intensity (in humans and animals) in China, 3) economic impact, 4) prevention and control, and 5) social impact. Disease specific information was obtained from 792 articles (637 in English and 155 in Chinese) and subject matter experts for the prioritization process. Following discussion of the OHZDP Tool output among disease experts, five priority zoonotic diseases were identified for China: avian influenza, echinococcosis, rabies, plague, and brucellosis. CONCLUSION: Representatives agreed on a list of five priority zoonotic diseases that can serve as a foundation to strengthen One Health collaboration for disease prevention and control in China; this list was developed prior to the emergence of SARS-CoV-2 and the COVID-19 pandemic. Next steps focused on establishing a multisectoral, One Health coordination mechanism, improving multisectoral linkages in laboratory testing and surveillance platforms, creating multisectoral preparedness and response plans, and increasing workforce capacity.

BACKGROUND: Timely and appropriate administration of post-exposure prophylaxis (PEP) is an essential component of human rabies prevention programs. We evaluated patient care at rabies clinics in a high-risk county in Hunan Province, China to inform strategies needed to achieve dog-mediated human rabies elimination by 2030. METHODS: We collected information on PEP, staff capacity, and service availability at the 17 rabies clinics in the high-risk county during onsite visits and key staff interviews. Additionally, we conducted observational assessments at five of these clinics, identified through purposive sampling to capture real-time information on patient care during a four-week period. Wound categories assigned by trained observers were considered accurate per national guidelines for comparison purposes. We used the kappa statistic and an alpha level of 0.05 to assess agreement between observers and clinic staff. RESULTS: In 2015, the 17 clinics provided PEP to 5,261 patients. Although rabies vaccines were available at all 17 clinics, rabies immune globulin (RIG) was only available at the single urban clinic in the county. During the assessment period in 2016, 196 patients sought care for possible rabies virus exposures. According to observers, 88 (44%) patients had category III wounds, 104 (53%) had category II wounds and 4 (2%) had category I wounds. Observers and PEP clinic staff agreed on approximately half of the assigned wound categories (kappa = 0.55, p-value< 0.001). Agreement for the urban county-level CDC clinic (kappa = 0.93, p-value<0.001) was higher than that of the rural township clinics (kappa = 0.16, p-value = 0.007). Using observer assigned wound categories, 142 (73%) patients received rabies vaccinations and RIG as outlined in the national guidelines. CONCLUSION: Rabies PEP services were available at each town of the project county; however, gaps between clinical practice of PEP and recommendations of national rabies guidelines were identified. We used these findings to develop and implement a training to rabies clinic staff on wound categorization, wound care, and appropriate use of PEP. Additional risk-based approaches for evaluating human rabies virus exposures may be needed as China progresses towards elimination.

Mass gatherings create settings conducive to infectious disease transmission. Empirical data to model infectious disease transmission at mass gatherings are limited. Video-analysis technology could be used to generate data on social mixing patterns needed for simulating influenza transmission at mass gatherings. We analyzed short video recordings of persons attending the GameFest event at a university in Troy, New York, in April 2013 to demonstrate the feasibility of this approach. Attendees were identified and tracked during three randomly selected time periods using an object-tracking algorithm. Tracks were analyzed to calculate the number and duration of unique pairwise contacts. A contact occurred each time two attendees were within 2 m of each other. We built and tested an agent-based stochastic influenza simulation model assuming two scenarios of mixing patterns in a geospatially accurate representation of the event venue -one calibrated to the mean cumulative contact duration estimated from GameFest video recordings and the other using a uniform mixing pattern. We compared one-hour attack rates (i.e., becoming infected) generated from these two scenarios following the introduction of a single infectious seed. Across the video recordings, 278 attendees were identified and tracked, resulting in 1,247 unique pairwise contacts with a cumulative mean contact duration of 74.76 s (SD: 80.71). The one-hour simulated mean attack rates were 2.17 % (95 % CI:1.45 - 2.82) and 0.21 % (95 % CI: 0.14 - 0.28) in the calibrated and uniform mixing model scenarios, respectively. We simulated influenza transmission at the GameFest event using social mixing data objectively captured through video-analysis technology. Microlevel geospatially accurate simulations can be used to assess the layout of event venues on social mixing and disease transmission. Future work can expand on this demonstration project to larger spatial and temporal scenes in more diverse settings.

In 2015, China and other member states of the United Nations adopted the goal of eliminating dog-mediated rabies by 2030. China has made substantial progress in reducing dog-mediated human rabies since peaking with more than 3,300 reported cases in 2007. To further improve coordination and planning, the Chinese Center for Disease Control and Prevention, in collaboration with the United States Centers for Disease Control and Prevention, conducted a Stepwise Approach towards Rabies Elimination (SARE) assessment in March 2019. Assessment goals included outlining progress and identifying activities critical for eliminating dog-mediated rabies. Participants representing national, provincial and local human and animal health sectors in China used the SARE assessment tool to answer 115 questions about the current dog-mediated rabies control and prevention programs in China. The established surveillance system for human rabies cases and availability of post-exposure prophylaxis were identified as strengths. Low dog vaccination coverage and limited laboratory confirmation of rabid dogs were identified gaps, resulting in an overall score of 1.5 on a scale of 0 to 5. Participants outlined steps to increase cross-sectoral information sharing, improve surveillance for dog rabies, increase dog vaccination coverage, and increase laboratory capacity to diagnose rabies at the provincial level. All assessment participants committed to strengthening cross-sector collaboration using a One Health approach to achieve dog-mediated human rabies elimination by 2030.

Previous research on respiratory infection transmission among university students has primarily focused on influenza. In this study, we explore potential transmission events for multiple respiratory pathogens in a social contact network of university students. University students residing in on-campus housing (n = 590) were followed for the development of influenza-like illness for 10-weeks during the 2012-13 influenza season. A contact network was built using weekly self-reported contacts, class schedules, and housing information. We considered a transmission event to have occurred if students were positive for the same pathogen and had a network connection within a 14-day period. Transmitters were individuals who had onset date prior to their infected social contact. Throat and nasal samples were analysed for multiple viruses by RT-PCR. Five viruses were involved in 18 transmission events (influenza A, parainfluenza virus 3, rhinovirus, coronavirus NL63, respiratory syncytial virus). Transmitters had higher numbers of co-infections (67%). Identified transmission events had contacts reported in small classes (33%), dormitory common areas (22%) and dormitory rooms (17%). These results suggest that targeting person-to-person interactions, through measures such as isolation and quarantine, could reduce transmission of respiratory infections on campus.

Although non-Hispanic American Indian and Alaska Native (AI/AN) persons account for 0.7% of the U.S. population,* a recent analysis reported that 1.3% of coronavirus disease 2019 (COVID-19) cases reported to CDC with known race and ethnicity were among AI/AN persons (1). To assess the impact of COVID-19 among the AI/AN population, reports of laboratory-confirmed COVID-19 cases during January 22(†)-July 3, 2020 were analyzed. The analysis was limited to 23 states(§) with >70% complete race/ethnicity information and five or more laboratory-confirmed COVID-19 cases among both AI/AN persons (alone or in combination with other races and ethnicities) and non-Hispanic white (white) persons. Among 424,899 COVID-19 cases reported by these states, 340,059 (80%) had complete race/ethnicity information; among these 340,059 cases, 9,072 (2.7%) occurred among AI/AN persons, and 138,960 (40.9%) among white persons. Among 340,059 cases with complete patient race/ethnicity data, the cumulative incidence among AI/AN persons in these 23 states was 594 per 100,000 AI/AN population (95% confidence interval [CI] = 203-1,740), compared with 169 per 100,000 white population (95% CI = 137-209) (rate ratio [RR] = 3.5; 95% CI = 1.2-10.1). AI/AN persons with COVID-19 were younger (median age = 40 years; interquartile range [IQR] = 26-56 years) than were white persons (median age = 51 years; IQR = 32-67 years). More complete case report data and timely, culturally responsive, and evidence-based public health efforts that leverage the strengths of AI/AN communities are needed to decrease COVID-19 transmission and improve patient outcomes.

BACKGROUND: Monitoring hepatitis B surveillance data is important for evaluating progress towards global hepatitis B elimination goals. Accurate classification of acute and chronic hepatitis infections is essential for assessing program effectiveness. METHODS: We evaluated hepatitis B case-reporting at six hospitals in Fujian, Hainan and Gansu provinces in 2015 to assess the accuracy of case classification. We linked National Notifiable Disease Reporting System (NNDRS) HBV case-reports with hospital information systems and extracted information on age, gender, admission ward and viral hepatitis diagnosis from medical records. To assess accuracy, we compared NNDRS reported case-classifications with the national HBV case definitions. Multivariable logistic regression was used to identify factors associated with misclassification. RESULTS: Of the 1420 HBV cases reported to NNDRS, 23 (6.5%) of the 352 acute reports and 648 (60.7%) of the 1068 chronic reports were correctly classified. Of the remaining, 318 (22.4%) were misclassified and 431 (30.4%) could not be classified due to the lack of supporting information. Based on the multivariable analysis, HBV cases reported from Hainan (aOR = 1.8; 95% CI: 1.3-2.4) and Gansu (aOR = 12.7; 95% CI: 7.7-20.1) along with reports from grade 2 hospitals (aOR = 1.6; 95% CI:1.2-2.2) and those from non-HBV related departments (aOR = 5.3; 95% CI: 4.1-7.0) were independently associated with being 'misclassified' in NNDRS. CONCLUSIONS: We identified discrepancies in the accuracy of HBV case-reporting in the project hospitals. Onsite training on the use of anti-HBc IgM testing as well as on HBV case definitions and reporting procedures are needed to accurately assess program effectiveness and ensure case-patients are referred to appropriate treatment and care. Routine surveillance evaluations such as this can be useful for improving data quality and monitoring program effectiveness.

Global spread of Zika virus in 2015 and 2016 highlighted the importance of surveillance to rapidly detect, report, and respond to emerging infections. We describe the lessons learned from the development and deployment of a web-based surveillance reporting system for Zika virus and other acute febrile illnesses (AFI) in Guangdong and Yunnan provinces, China. In less than 2 months, we customized the China Epidemiologic Dynamic Data Collection (EDDC) platform to collect, manage, and visualize data in close to real time. According to provincial and sentinel hospital staff requirements, the customized platform provided specific user authorization management, online/offline data collection, data quality control, and secure data transmission and protection and visualization tools. AFI case data and laboratory test results were entered through a web-based interface by hospital and provincial-level staff and saved on a China CDC server in Beijing. The dashboard visualized aggregate data by hospital, age, onset date, and laboratory test results. From June 2017 to December 2018, data from 768 patients with AFI were entered into the web-based surveillance system and visualized by hospital and provincial-level decision makers. Input from provincial and hospital staff was essential for developing the AFI case-reporting and feedback tools appropriate for specific settings and decision-making requirements. Web-based systems (eg, EDDC, data collection, and visualization tools that can be easily adapted to meet local surveillance needs) can help shorten time for system deployment, thereby strengthening global health security to rapidly detect and respond to emerging infections and outbreaks.

Background: Strong laboratory capacity is essential for detecting and responding to emerging and re-emerging global health threats. We conducted a quantitative laboratory assessment during 2014-2015 in two resource-limited provinces in southern China, Guangxi and Guizhou in order to guide strategies for strengthening core capacities as required by the International Health Regulations (IHR 2005). Methods: We selected 28 public health and clinical laboratories from the provincial, prefecture and county levels through a quasi-random sampling approach. The 11-module World Health Organization (WHO) laboratory assessment tool was adapted to the local context in China. At each laboratory, modules were scored 0-100% through a combination of paper surveys, in-person interviews, and visual inspections. We defined module scores as strong (> = 85%), good (70-84%), weak (50-69%), and very weak (< 50%). We estimated overall capacity and compared module scores across the provincial, prefecture, and county levels. Results: Overall, laboratories in both provinces received strong or good scores for 10 of the 11 modules. These findings were primarily driven by strong and good scores from the two provincial level laboratories; prefecture and county laboratories were strong or good for only 8 and 6 modules, respectively. County laboratories received weak scores in 4 modules. The module, 'Public Health Functions' (e.g., surveillance and reporting practices) lagged far behind all other modules (mean score = 46%) across all three administrative levels. Findings across the two provinces were similar. Conclusions: Laboratories in Guangxi and Guizhou are generally performing well in laboratory capacity as required by IHR. However, we recommend targeted interventions particularly for county-level laboratories, where we identified a number of gaps. Given the importance of surveillance and reporting, addressing gaps in public health functions is likely to have the greatest positive impact for IHR requirements. The quantitative WHO laboratory assessment tool was useful in identifying both comparative strengths and weaknesses. However, prior to future assessments, the tool may need to be aligned with the new WHO IHR monitoring and evaluation framework.

OBJECTIVE: The WHO estimates that almost 40% of patients diagnosed with tuberculosis (TB) are not reported. We implemented this study to assess TB under-reporting and delayed treatment registration in nine counties in China. DESIGN: A retrospective inventory study (record review). SETTING: Counties were selected using purposive sampling from nine provinces distributed across eastern, central and western regions of China in 2015. PRIMARY AND SECONDARY OUTCOME MEASURES: Under-reporting was calculated as the percentage of patients with TB not reported to TB Information Management System (TBIMS) within 6 months of diagnosis. Delayed registration was estimated as the percentage of reported cases initiating treatment 7 or more days after diagnosis. Multivariable logistic regression and an alpha level of 0.05 were used to examine factors associated with these outcomes. RESULTS: Of the 5606 patients with TB identified from project health facilities and social insurance systems, 1082 (19.3%) were not reported to TBIMS. Of the 4524 patients successfully reported, 1416 (31.3%) were not registered for treatment within 7 days of diagnosis. Children, TB pleurisy, patients diagnosed in the eastern and central regions and patients with a TB diagnosis recorded in either health facilities or social insurance system-but not both-were statistically more likely to be unreported. Delayed treatment registration was more likely for previously treated patients with TB, patients with negative or unknown sputum results and for patients diagnosed in the eastern region. CONCLUSION: Almost one in every five patients diagnosed with TB in this study was unknown to local or national TB control programmes. We recommend strengthening TB data management practices, particularly in the eastern and central regions, and developing specific guidelines for reporting paediatric TB and TB pleurisy. Patient education and follow-up by diagnosing facilities could improve timely treatment registration. Additional studies are needed to assess under-reporting elsewhere in China.

BACKGROUND: Hand, Foot, and Mouth Disease (HFMD) is most frequently caused by Enterovirus71 (EV-A71) or Coxsackie virus A16 (CV-A16), infants and young children are at greatest risk. Describing the epidemiology of HFMD can help develop and better target interventions, including the use of pediatric EV-A71 vaccination. METHODS: We obtained data from the national surveillance system for HFMD cases with onset dates from 2009 to 2015. We defined probable cases as patient with skin papular or vesicular rashes on the hands, feet, mouth, or buttocks and confirmed cases as patients with the above symptoms along with laboratory-based enterovirus detection. We generated overall and age-specific annual incidence rates and described the temporal variability and seasonality of HFMD in Qinghai Province. We identified spatial clustering of HFMD incidence at the county level using the Local Indicator of Spatial Associationand an alpha level of 0.05. RESULTS: During the study period, 14,480 HFMD probable or confirmed cases were reported in Qinghai Province. Of the 2158 (14.9%) with laboratory confirmation, 924 (42.6%) were caused by CV-A16 and 830 (38.2%) were caused by EV-A71. The majority (89%) of all case-patients were </= 5 years of age and male (61.5%). The overall mean annual HFMD incidence rate was 36.4 cases per 100,000 populations, while the incidence rate for children </=5 years of age was 379.5 cases per 100,000. Case reports peaked during the months of May through July. HFMD was predominantly caused by EV-A71, except in 2010 and 2014 when CV-A16 was the predominant causative agent. High incidence rates of HFMD were clustered (Moran's I = 0.59, P < 0.05) in the eastern region of the province. CONCLUSION: HFMD remains an important cause of childhood disease in Qinghai Province, occurring in an acyclical pattern of increased incidence, primarily due to CV-A16 circulation every three years. Incidence is also seasonal and tends to spatially cluster in the eastern region of the province. Since approximately 40% of confirmed HFMD cases were due to EV-A71, EV-A71 vaccination is likely to have a positive impact on the HFMD disease burden. Routine analysis of local surveillance data is crucial for describing disease occurrence and changes in etiology.

We conducted a retrospective analysis of norovirus outbreaks reported to the National Public Health Emergency Event Surveillance System (PHEESS) in China from January 1, 2014 to December 31, 2017. We reviewed all acute gastroenteritis outbreaks (n = 692) submitted to PHEESS to identify the frequency, seasonality, geographic distribution, setting, and transmission mode of outbreaks due to norovirus. A total of 616 norovirus outbreaks resulting in 30,848 cases were reported. Among these outbreaks, 571 (93%) occurred in school settings including 239 (39%) in primary schools, 136 (22%) in childcare facilities, and 121 (20%) in secondary schools. The majority of outbreaks (63%) were due to person-to-person transmission, followed by multiple modes of transmission (11%), foodborne (5%) and waterborne (3%) transmission. These findings highlight the importance of improving hand hygiene and environmental disinfection in high-risk settings. Developing a standard and quantitative outbreak reporting structure could improve the usefulness of PHEESS for monitoring norovirus outbreaks.

BACKGROUND: Streptococcus pneumoniae (Sp) is a leading cause of bacterial pneumonia, meningitis, and sepsis and a major source of morbidity and mortality worldwide. Invasive pneumococcal disease (IPD) is defined as isolation of Sp from a normally sterile site, including blood or cerebrospinal fluid. The aim of this study is to describe outcomes as well as clinical and epidemiological characteristics of hospitalized IPD case patients in central China. METHODS: We conducted surveillance for IPD among children and adults from April 5, 2010 to September 30, 2012, in four major hospitals in Jingzhou City, Hubei Province. We collected demographic, clinical, and outcome data for all enrolled hospitalized patients with severe acute respiratory infection (SARI) or meningitis, and collected blood, urine, and cerebrospinal fluid (CSF) for laboratory testing for Sp infections. Collected data were entered into Epidata software and imported into SPSS for analysis. RESULTS: We enrolled 22,375 patients, including 22,202 (99%) with SARI and 173 (1%) with meningitis. One hundred and eighteen (118, 3%) with either SARI or meningitis were Sp positive, 32 (0.8%) from blood/CSF culture, and 87 (5%) from urine antigen testing. Of those 118 patients, 57% were aged >/=65 years and nearly 100% received antibiotics during hospitalization. None were previously vaccinated with 7-valent pneumococcal conjugate vaccine (PCV 7), 23-valent pneumococcal polysaccharide vaccine, or seasonal influenza vaccine. The main serotypes identified were 14, 12, 3, 1, 19F, 4, 5, 9V, 15 and 18C, corresponding to serotype coverage rates of 42%, 63%, and 77% for PCV7, PCV10, and PCV13, respectively. CONCLUSIONS: Further work is needed to expand access to pneumococcal vaccination in China, both among children and potentially among the elderly, and inappropriate use of antibiotics is a widespread and serious problem in China.

BACKGROUND: The prevalence, symptom course, and shedding in persons infected with the four most common human coronaviruses (HCoV) -229E, HKU1, NL63 and OC43 are poorly described OBJECTIVES: We estimate their prevalence and associated symptoms among college students identified via a social network study design. PATIENTS/METHODS: We collected 1-3 samples (n=250 specimens) from 176 participants between October 2012 and January 17, 2013: participants with acute respiratory infection (ARI) (cough and body aches or chills or fever/feverishness) and their social contacts. Virus was detected using RT-PCR. RESULTS: 30.4% (76/250) of specimens tested positive for any virus tested and 4.8% (12/250) were positive for two or more viruses. Human coronaviruses (HCoVs [22.0%; 55/250]), rhinovirus (7.6%; 19/250), and influenza A (6.4%; 16/250) were most prevalent. Symptoms changed significantly over time among ARI participants with HCoV: the prevalence of cough and chills decreased over 6 days (p=0.04, and p=0.01, respectively), while runny nose increased over the same period (p=0.02). HCoV-NL63 was the most frequent virus detected 6 days following symptom onset (8.9%), followed by rhinovirus (6.7%). CONCLUSIONS: During a 3-month period covering a single season, HCoVs were common, even among social contacts without respiratory symptoms; specific symptoms may change over the course of HCoV-associated illness and were similar to symptoms from influenza and rhinovirus. This article is protected by copyright. All rights reserved.

Background: Clostridioides difficile infection (CDI) is an important cause of morbidity and mortality among hospitalized patients. In China, however, hospital staffdo not routinely test for CDI, leading to under-diagnosis and poor patient outcomes. Locally generated CDI data can help assess the magnitude of the problem and strengthen approaches for CDI prevention and control. Methods: We prospectively monitored hospital-onset hospital-associated (HOHA) CDI in four intensive care units (ICUs) from June 2013 to September 2014 in a large teaching hospital in China. We collected clinical information from all ICU patients with ≥ 3 episodes of diarrhea occurring within a 24-h period at least 48 h following admission (suspect case definition). Stool specimens were collected from all suspect cases of CDI and cultured for C. difficile. Polymerase chain reaction (PCR) was used to detect toxin genes from positive isolates; multi-locus sequence typing (MLST) was used for typing and identifying novel strains. We estimated the incidence rate as the number of HOHA CDI cases per 10,000 patient days; 95% confidence intervals were generated to assess rate differences between the four ICUs. Results: A total of 593 hospital-onset diarrhea patients met the suspect case definition during the study period. Of these, 47 patients (8%) were positive for C. difficile and toxin genes. The HOHA-CDI incidence rate was 14.1 cases per 10,000 patient days (95% CI: 10.5-18.6). Six patients with HOHA CDI died. ST54 (n = 14, 20%) was the most common type of HOHA-CDI strain circulating in the hospital during the study period and was linked to a temporal cluster (outbreak) involving two (NICU and GICU) of the four ICUs. Conclusion: HOHA-CDI occurs among ICU patients at this teaching hospital, supporting the importance of routine testing for CDI. Information on strain distribution can help detect CDI outbreaks. Detection of ST54 strain in a temporal cluster suggests possible gaps in infection control practices that should be investigated and addressed as needed.

INTRODUCTION: School closures, while an effective measure against the spread of disease during a pandemic, may carry unintended social and economic consequences for students and families. We evaluated these costs and consequences following a 4-day school closure in Mississippi's Harrison County School District (HCSD). METHODS: In a survey of all households with students enrolled in HCSD, we collected information on difficulties related to the school closure, including interruption of employment and pay, loss of access to subsidized school meals, and arrangement of alternative childcare. We analyzed this information in the context of certain demographic characteristics of the survey respondents and households, such as race, level of education, and income. We also estimated the average number of lost work days and documented the childcare alternatives chosen by households affected by the school closure. RESULTS: We received 2,229 (28.4%) completed surveys from an estimated 7,851 households eligible to participate. About half (1,082 [48.5%]) of the households experienced at least some difficulty during the closure, primarily in three areas: uncertainty about duration of the closure, lost income, and the effort of arranging alternate childcare. Adults working outside the home, particularly the major wage earner in the household, were more likely to suffer lost income while schools were closed, an effect mitigated by paid leave benefits. Difficulty arranging childcare was reported most frequently by respondents with lower levels of education and households with younger children. Beyond the top three concerns expressed by households in HCSD, the survey also shed light on the issue of food insecurity when subsidized school meals are not available. Reported by 17.9% of households participating in the subsidized school lunch program, difficulty providing meals during the closure was associated with higher numbers of dependent children, selection of "other" as the race of the household respondent, and lower levels of education. CONCLUSION: To help prevent undue financial hardship in families of school children, public health authorities and school administrators should provide recommendations for childcare alternatives and paid leave or remote work options during prolonged school closures, particularly to households in which all adults work outside of the home.

Mass gatherings create environments conducive to the transmission of infectious diseases. Thousands of mass gatherings are held annually in the United States; however, information on the frequency and characteristics of respiratory disease outbreaks and on the use of nonpharmaceutical interventions at these gatherings is scarce. We administered an online assessment to the 50 state health departments and 31 large local health departments in the United States to gather information about mass gathering-related respiratory disease outbreaks occurring between 2009 and 2014. The assessment also captured information on the use of nonpharmaceutical interventions to slow disease transmission in these settings. We downloaded respondent data into a SAS dataset for descriptive analyses. We received responses from 43 (53%) of the 81 health jurisdictions. Among these, 8 reported 18 mass gathering outbreaks. More than half (n = 11) of the outbreaks involved zoonotic transmission of influenza A (H3N2v) at county and state fairs. Other outbreaks occurred at camps (influenza A (H1N1)pdm09 [n = 2] and A (H3) [n = 1]), religious gatherings (influenza A (H1N1)pdm09 [n = 1] and unspecified respiratory virus [n = 1]), at a conference (influenza A (H1N1)pdm09), and a sporting event (influenza A). Outbreaks ranged from 5 to 150 reported cases. Of the 43 respondents, 9 jurisdictions used nonpharmaceutical interventions to slow or prevent disease transmission. Although respiratory disease outbreaks with a large number of cases occur at many types of mass gatherings, our assessment suggests that such outbreaks may be uncommon, even during the 2009 influenza A (H1N1) pandemic, which partially explains the reported, but limited, use of nonpharmaceutical interventions. More research on the characteristics of mass gatherings with respiratory disease outbreaks and effectiveness of nonpharmaceutical interventions would likely be beneficial for decision makers at state and local health departments when responding to future outbreaks and pandemics.

Background. School closures are an important mitigation strategy during influenza pandemic: if implemented early in a local outbreak, they can slow the disease spread in the surrounding community. During seasonal influenza epidemics, school closures may occur reactively, after the disease is already widespread in the community. Such reactive closures are often too late to reduce influenza transmission. However, they can provide data to determine under which circumstances they might be effective in reducing influenza-like illness (ILI) transmission. Methods. We conducted a household survey in a school district in Kentucky. District A closed after high student absenteeism due to influenza-like illness (ILI), whereas adjacent Districts B and C remained open. We collected data on self-reported ILI among household members in these 3 districts 2 weeks before the District A closure, during closure, and 2 weeks after reopening, and we evaluated economic and social consequences of school closure on student households in District A. The difference-in-differences method was applied to compare changes in ILI rates from before to after closure between districts. Results. Estimated average daily ILI rate decreased less in District A than in District B or C for the entire sample and when stratified by age groups (0-5 years old, 6-18 years old, and above 18 years old). Twenty-five percent of District A households reported ≥1 closure-related economic or social difficulty. Conclusions. Closing schools after a widespread ILI activity in District A did not reduce ILI transmission but caused difficulties for some households.

BACKGROUND: During an influenza pandemic, the United States Centers for Disease Control and Prevention (CDC) may recommend school closures. These closures could have unintended consequences for students and their families. Publicly available social media could be analyzed to identify the consequences of an unplanned school closure. METHODS: As a proxy for an unplanned, pandemic-related school closure, we used the district-wide school closure due to the September 10-18, 2012 teachers' strike in Chicago, Illinois. We captured social media posts about the school closure using the Radian6 social media-monitoring platform. An online workforce from Amazon Mechanical Turk categorized each post into one of two groups. The first group included relevant posts that described the impact of the closure on students and their families. The second group included irrelevant posts that described the political aspects of the strike or topics unrelated to the school closure. All relevant posts were further categorized as expressing a positive, negative, or neutral sentiment. We analyzed patterns of relevant posts and sentiment over time and compared our findings to household surveys conducted after other unplanned school closures. RESULTS: We captured 4,546 social media posts about the district-wide school closure using our search criteria. Of these, 930 (20%) were categorized as relevant by the online workforce. Of the relevant posts, 619 (67%) expressed a negative sentiment, 51 (5%) expressed a positive sentiment, and 260 (28%) were neutral. The number of relevant posts, and especially those with a negative sentiment, peaked on day 1 of the strike. Negative sentiment expressed concerns about childcare, missed school lunches, and the lack of class time for students. This was consistent with findings from previously conducted household surveys. CONCLUSION: Social media are publicly available and can readily provide information on the impact of an unplanned school closure on students and their families. Using social media to assess the impact of an unplanned school closure due to a public health event would be informative. An online workforce can effectively assist with the review process.

BACKGROUND: Because mass gatherings create environments conducive for infectious disease transmission, public health officials may recommend postponing or canceling large gatherings during a moderate or severe pandemic. Despite these recommendations, limited empirical information exists on the frequency and characteristics of mass gathering-related respiratory disease outbreaks occurring in the United States. METHODS: We conducted a systematic literature review to identify articles about mass gathering-related respiratory disease outbreaks occurring in the United States from 2005 to 2014. A standard form was used to abstract information from relevant articles identified from six medical, behavioral and social science literature databases. We also analyzed data from the National Outbreaks Reporting System (NORS), maintained by the Centers for Disease Control and Prevention since 2009, to estimate the frequency of mass gathering-related respiratory disease outbreaks reported to the system. RESULTS: We identified 21 published articles describing 72 mass gathering-related respiratory disease outbreaks. Of these 72, 40 (56%) were associated with agriculture fairs and Influenza A H3N2v following probable swine exposure, and 25 (35%) with youth summer camps and pandemic Influenza A H1N1. Outbreaks of measles (n = 1) and mumps (n = 2) were linked to the international importation of disease. Between 2009 and 2013, 1,114 outbreaks were reported to NORS, including 96 respiratory disease outbreaks due to Legionella. None of these legionellosis outbreaks was linked to a mass gathering according to available data. CONCLUSION: Mass gathering-related respiratory disease outbreaks may be uncommon in the United States, but have been reported from fairs (zoonotic transmission) as well as at camps where participants have close social contact in communal housing. International importation can also be a contributing factor. NORS collects information on certain respiratory diseases and could serve as a platform to monitor mass gathering-related respiratory outbreaks in the future.

Estimates of contact among children, used for infectious disease transmission models and understanding social patterns, historically rely on self-report logs. Recently, wireless sensor technology has enabled objective measurement of proximal contact and comparison of data from the two methods. These are mostly small-scale studies, and knowledge gaps remain in understanding contact and mixing patterns and also in the advantages and disadvantages of data collection methods. We collected contact data from a middle school, with 7th and 8th grades, for one day using self-report contact logs and wireless sensors. The data were linked for students with unique initials, gender, and grade within the school. This paper presents the results of a comparison of two approaches to characterize school contact networks, wireless proximity sensors and self-report logs. Accounting for incomplete capture and lack of participation, we estimate that "sensor-detectable", proximal contacts longer than 20 seconds during lunch and class-time occurred at 2 fold higher frequency than "self-reportable" talk/touch contacts. Overall, 55% of estimated talk-touch contacts were also sensor-detectable whereas only 15% of estimated sensor-detectable contacts were also talk-touch. Contacts detected by sensors and also in self-report logs had longer mean duration than contacts detected only by sensors (6.3 vs 2.4 minutes). During both lunch and class-time, sensor-detectable contacts demonstrated substantially less gender and grade assortativity than talk-touch contacts. Hallway contacts, which were ascertainable only by proximity sensors, were characterized by extremely high degree and short duration. We conclude that the use of wireless sensors and self-report logs provide complementary insight on in-school mixing patterns and contact frequency.

Students attending schools play an important role in the transmission of influenza. In this study, we present a social network analysis of contacts among 1,828 students in eight different schools in urban and suburban areas in and near Pittsburgh, Pennsylvania, United States of America, including elementary, elementary-middle, middle, and high schools. We collected social contact information of students who wore wireless sensor devices that regularly recorded other devices if they are within a distance of 3 meters. We analyzed these networks to identify patterns of proximal student interactions in different classes and grades, to describe community structure within the schools, and to assess the impact of the physical environment of schools on proximal contacts. In the elementary and middle schools, we observed a high number of intra-grade and intra-classroom contacts and a relatively low number of inter-grade contacts. However, in high schools, contact networks were well connected and mixed across grades. High modularity of lower grades suggests that assumptions of homogeneous mixing in epidemic models may be inappropriate; whereas lower modularity in high schools suggests that homogenous mixing assumptions may be more acceptable in these settings. The results suggest that interventions targeting subsets of classrooms may work better in elementary schools than high schools. Our work presents quantitative measures of age-specific, school-based contacts that can be used as the basis for constructing models of the transmission of infections in schools.

BACKGROUND: Social networks are increasingly recognized as important points of intervention, yet relatively few intervention studies of respiratory infection transmission have utilized a network design. Here we describe the design, methods, and social network structure of a randomized intervention for isolating respiratory infection cases in a university setting over a 10-week period. METHODOLOGY/PRINCIPAL FINDINGS: 590 students in six residence halls enrolled in the eX-FLU study during a chain-referral recruitment process from September 2012-January 2013. Of these, 262 joined as "seed" participants, who nominated their social contacts to join the study, of which 328 "nominees" enrolled. Participants were cluster-randomized by 117 residence halls. Participants were asked to respond to weekly surveys on health behaviors, social interactions, and influenza-like illness (ILI) symptoms. Participants were randomized to either a 3-Day dorm room isolation intervention or a control group (no isolation) upon illness onset. ILI cases reported on their isolation behavior during illness and provided throat and nasal swab specimens at onset, day-three, and day-six of illness. A subsample of individuals (= 103) participated in a sub-study using a novel smartphone application, iEpi, which collected sensor and contextually-dependent survey data on social interactions. Within the social network, participants were significantly positively assortative by intervention group, enrollment type, residence hall, iEpi participation, age, gender, race, and alcohol use (all P < 0.002). CONCLUSIONS/SIGNIFICANCE: We identified a feasible study design for testing the impact of isolation from social networks in a university setting. These data provide an unparalleled opportunity to address questions about isolation and infection transmission, as well as insights into social networks and behaviors among college-aged students. Several important lessons were learned over the course of this project, including feasible isolation durations, the need for extensive organizational efforts, as well as the need for specialized programmers and server space for managing survey and smartphone data.

In the United States, influenza season typically begins in October or November, peaks in February, and tapers off in April. During the winter holiday break, from the end of December to the beginning of January, changes in social mixing patterns, healthcare-seeking behaviors, and surveillance reporting could affect influenza-like illness (ILI) rates. We compared predicted with observed weekly ILI to examine trends around the winter break period. We examined weekly rates of ILI by region in the United States from influenza season 2003-2004 to 2012-2013. We compared observed and predicted ILI rates from week 44 to week 8 of each influenza season using the auto-regressive integrated moving average (ARIMA) method. Of 1,530 region, week, and year combinations, 64 observed ILI rates were significantly higher than predicted by the model. Of these, 21 occurred during the typical winter holiday break period (weeks 51-52); 12 occurred during influenza season 2012-2013. There were 46 observed ILI rates that were significantly lower than predicted. Of these, 16 occurred after the typical holiday break during week 1, eight of which occurred during season 2012-2013. Of 90 (10 HHS regions x 9 seasons) predictions during the peak week, 78 predicted ILI rates were lower than observed. Out of 73 predictions for the post-peak week, 62 ILI rates were higher than observed. There were 53 out of 73 models that had lower peak and higher post-peak predicted ILI rates than were actually observed. While most regions had ILI rates higher than predicted during winter holiday break and lower than predicted after the break during the 2012-2013 season, overall there was not a consistent relationship between observed and predicted ILI around the winter holiday break during the other influenza seasons.

Influenza poses a significant health threat to children, and schools may play a critical role in community outbreaks. Mathematical outbreak models require assumptions about contact rates and patterns among students, but the level of temporal granularity required to produce reliable results is unclear. We collected objective contact data from students aged 5-14 at an elementary school and middle school in the state of Utah, USA, and paired those data with a novel, data-based model of influenza transmission in schools. Our simulations produced within-school transmission averages consistent with published estimates. We compared simulated outbreaks over the full resolution dynamic network with simulations on networks with averaged representations of contact timing and duration. For both schools, averaging the timing of contacts over one or two school days caused average outbreak sizes to increase by 1-8%. Averaging both contact timing and pairwise contact durations caused average outbreak sizes to increase by 10% at the middle school and 72% at the elementary school. Averaging contact durations separately across within-class and between-class contacts reduced the increase for the elementary school to 5%. Thus, the effect of ignoring details about contact timing and duration in school contact networks on outbreak size modelling can vary across different schools.

OBJECTIVE: From January 29 through February 5, 2013, a school district outside metropolitan Denver, Colorado, was closed because of absenteeism related to influenza-like illness (ILI) among students and staff. We evaluated the consequences and acceptability of the closure among affected households. METHODS: We conducted a household survey regarding parent or guardian employment and income interruptions, alternative child care arrangements, interruption of noneducational school services, ILI symptoms, student re-congregation, and communication preferences during the closure. RESULTS: Of the 35 (31%) of 113 households surveyed, the majority (28 [80%]) reported that the closure was not challenging. Seven (20%) households reported challenges: 5 (14%) reported that 1 or more adults missed work, 3 (9%) reported lost pay, and 1 (3%) reported challenges because of missed subsidized school meals. The majority (22 [63%]) of households reported that a hypothetical 1-month closure would not represent a problem; 6 of 8 households that did anticipate challenges reported that all adults worked outside the home. The majority (58%) of students visited at least 1 outside venue during the closure. CONCLUSIONS: A brief school closure did not pose a major problem for the majority of the affected households surveyed. School and public health officials should consider the needs of families in which all adults work outside the home when creating school closure contingency plans.