An outbreak of measles in the Netherlands in 2013–2014 provided an opportunity to assess the effect of MMR vaccination on severity and infectiousness of measles.

Measles is notifiable in the Netherlands. We used information on vaccination, hospitalisation, complications, and most likely source(s) of infection from cases notified during the outbreak. When a case was indicated as a likely source for at least one other notified case, we defined it as infectious. We estimated the age-adjusted effect of vaccination on severity and infectiousness with logistic regression.

Of 2676 notified cases, 2539 (94.9%) were unvaccinated, 121 (4.5%) were once-vaccinated and 16 (0.6%) were at least twice-vaccinated; 328 (12.3%) cases were reported to have complications and 172 (6.4%) cases were hospitalised. Measles in twice-vaccinated cases led less often to complications and/or hospitalisation than measles in unvaccinated cases (0% and 14.5%, respectively, aOR 0.1 (95% CI 0–0.89), P = 0.03). Of unvaccinated, once-vaccinated and twice-vaccinated cases, respectively, 194 (7.6%), seven (5.1%) and 0 (0%) were infectious. These differences were not statistically significant (P > 0.05).

Our findings suggest a protective effect of vaccination on the occurrence of complications and/or hospitalisation as a result of measles and support the WHO recommendation of a two-dose MMR vaccination schedule.

COVID-19 as an emerging disease has spread to 183 countries and territories worldwide as of 20 March 2020. The first COVID-19 case (i.e. the index case) in Iran was observed in the city of Qom on 19 February 2020. One of the cities of Markazi Province is Delijan, which shares a border with Qom. Consequently, COVID-19 has quickly spread in this city because a large population commutes daily between the two cities. This study aimed to report the challenges and considerations of community-based preparedness at the onset of COVID-19 outbreak in a city of Iran in 2020.

Participation in European surveillance for bloodstream infection (BSI) commenced in Ireland in 1999 with all laboratories (n = 39) participating by 2014. Observational hand hygiene auditing (OHHA) was implemented in 2011. The aim of this study was to evaluate the impact of OHHA on hand hygiene compliance, alcohol hand rub (AHR) procurement and the incidence of sensitive and resistant Staphylococcus aureus and Enterococcus faecium and faecalis BSI. A prospective segmented regression analysis was performed to determine the temporal association between OHHA and outcomes. Observed hand hygiene improved from 74.7% (73.7–75.6) in 2011 to 90.8% (90.1–91.3) in 2016. AHR procurement increased from 20.1 l/1000 bed days used (BDU) in 2009 to 33.2 l/1000 BDU in 2016. A pre-intervention reduction of 2% per quarter in the ratio of methicillin sensitive Staphylococcus aureus BSI/BDU stabilized in the time period after the intervention (P < 0.01). The ratio of Methicillin resistant Staphylococcus aureus (MRSA) BSI/BDU was decreasing by 5% per quarter pre-intervention, this slowed to 2% per quarter post intervention, (P < 0.01). There was no significant change in the ratio of vancomycin sensitive (P = 0.49) or vancomycin resistant (P = 0.90) Enterococcus sp. BSI/BDU post intervention. This study shows national OHHA increased observed hand hygiene compliance and AHR procurement, however there was no associated reduction in BSI.

The aim of this study was to develop and externally validate a simple-to-use nomogram for predicting the survival of hospitalised human immunodeficiency virus/acquired immunodeficiency syndrome (HIV/AIDS) patients (hospitalised person living with HIV/AIDS (PLWHAs)). Hospitalised PLWHAs (n = 3724) between January 2012 and December 2014 were enrolled in the training cohort. HIV-infected inpatients (n = 1987) admitted in 2015 were included as the external-validation cohort. The least absolute shrinkage and selection operator method was used to perform data dimension reduction and select the optimal predictors. The nomogram incorporated 11 independent predictors, including occupation, antiretroviral therapy, pneumonia, tuberculosis, Talaromyces marneffei, hypertension, septicemia, anaemia, respiratory failure, hypoproteinemia and electrolyte disturbances. The Likelihood χ2 statistic of the model was 516.30 (P = 0.000). Integrated Brier Score was 0.076 and Brier scores of the nomogram at the 10-day and 20-day time points were 0.046 and 0.071, respectively. The area under the curves for receiver operating characteristic were 0.819 and 0.828, and precision-recall curves were 0.242 and 0.378 at two time points. Calibration plots and decision curve analysis in the two sets showed good performance and a high net benefit of nomogram. In conclusion, the nomogram developed in the current study has relatively high calibration and is clinically useful. It provides a convenient and useful tool for timely clinical decision-making and the risk management of hospitalised PLWHAs.

California has a large population of people experiencing homelessness (PEH) that is characterised by a high proportion of people who are unsheltered and chronically homeless. PEH are at increased risk of communicable diseases due to multiple, intersecting factors, including increased exposures, comorbid conditions including substance use disorder and mental illness and lack of access to hygiene and healthcare facilities. Data available for several communicable diseases show that PEH in California experiences an increased burden of communicable diseases compared to people not experiencing homelessness. Public health agencies face unique challenges in serving this population. Efforts to reduce homelessness, increase access to health care for PEH, enhance data availability and strengthen partnerships among agencies serving PEH can help reduce the disparity in communicable disease burden faced by PEH.

Chills and vomiting have traditionally been associated with severe bacterial infections and bacteremia. However, few modern studies have in a prospective way evaluated the association of these signs with bacteremia, which is the aim of this prospective, multicenter study. Patients presenting to the emergency department with at least one affected vital sign (increased respiratory rate, increased heart rate, altered mental status, decreased blood pressure or decreased oxygen saturation) were included. A total of 479 patients were prospectively enrolled. Blood cultures were obtained from 197 patients. Of the 32 patients with a positive blood culture 11 patients (34%) had experienced shaking chills compared with 23 (14%) of the 165 patients with a negative blood culture, P = 0.009. A logistic regression was fitted to show the estimated odds ratio (OR) for a positive blood culture according to shaking chills. In a univariate model shaking chills had an OR of 3.23 (95% CI 1.35–7.52) and in a multivariate model the OR was 5.9 (95% CI 2.05–17.17) for those without prior antibiotics adjusted for age, sex, and prior antibiotics. The presence of vomiting was also addressed, but neither a univariate nor a multivariate logistic regression showed any association between vomiting and bacteremia. In conclusion, among patients at the emergency department with at least one affected vital sign, shaking chills but not vomiting were associated with bacteremia.

There has been no study exploring the prognostic values of neutrophil percentage-to-albumin ratio (NPAR). We hypothesised that NPAR is a novel marker of inflammation and is associated with all-cause mortality in patients with severe sepsis or septic shock. Patient data were extracted from the MIMIC-III V1.4 database. Only the data for the first intensive care unit (ICU) admission of each patient were used and baseline data were extracted within 24 h after ICU admission. The clinical endpoints were 30-, 90- and 365-day all-cause mortality in critically ill patients with severe sepsis or septic shock. Cox proportional hazards models and subgroup analyses were used to determine the relationship between NPAR and these clinical endpoints. A total of 2166 patients were eligible for this analysis. In multivariate analysis, after adjustments for age, ethnicity and gender, higher NPAR was associated with increased risk of 30-, 90- and 365-day all-cause mortality in critically ill patients with severe sepsis or septic shock. Furthermore, after adjusting for more confounding factors, higher NPAR remained a significant predictor of all-cause mortality (tertile 3 vs. tertile 1: HR, 95% CI: 1.29, 1.04–1.61; 1.41, 1.16–1.72; 1.44, 1.21–1.71). A similar trend was observed in NPAR levels stratified by quartiles. Higher NPAR was associated with increased risk of all-cause mortality in critically ill patients with severe sepsis or septic shock.

Tuberculosis (TB) in children is a critical public health issue. In Bohol, Philippines, we found a high tuberculin skin test (TST)-positive prevalence (weighted prevalence = 6.4%) among 5476 children (<15 years) from 184 villages, with geographically isolated communities having prevalence as high as 29%. Therefore, we conducted a geospatial and hot spot analysis to examine the association between villages with high TST-positive prevalence (⩾6.5%) and access to medical care (distance (in kilometres and minutes of travel time) to the municipal Rural Health Units (RHU)), access to healthcare resources (distance to Provincial Health Office (PHO)) and socioeconomic determinants of health. Hot spot analysis revealed significant clusters of TST-positive prevalence in villages farthest from the PHO. Based on univariate analysis, the following variables associated with high prevalence were included in the multivariate model: minutes of travel time to the PHO, distance to the PHO, island villages and total deprivation based on socioeconomic indicators. In the final model, only distance to PHO in minutes was significant (P = 0.005). When evaluated further, greater than 1-hour drive significantly increased risk for TST-positivity (P = 0.003). Distance to healthcare resources likely increases the risk of TB transmission within the community. Expanding TB control efforts to geographically isolated areas is critical.

Nipah virus (NiV) outbreak occurred in Kozhikode district, Kerala, India in 2018 with a case fatality rate of 91% (21/23). In 2019, a single case with full recovery occurred in Ernakulam district. We described the response and control measures by the Indian Council of Medical Research and Kerala State Government for the 2019 NiV outbreak. The establishment of Point of Care assays and monoclonal antibodies administration facility for early diagnosis, response and treatment, intensified contact tracing activities, bio-risk management and hospital infection control training of healthcare workers contributed to effective control and containment of NiV outbreak in Ernakulam.

Studies on community-acquired pneumonia (CAP) and pneumococcal pneumonia (PP) related to the 13-valent pneumococcal conjugate vaccine (PCV13) introduction in Asia are scarce. This study aimed to investigate the epidemiological and microbiological determinants of hospitalised CAP and PP after PCV13 was introduced in Japan. This observational hospital-based surveillance study included children aged ⩽15 years, admitted to hospitals in and around Chiba City, Japan. Participants had bacterial pneumonia based on a positive blood or sputum culture for bacterial pathogens. Serotype and antibiotic-susceptibility testing of Streptococcus pneumoniae and Haemophilus influenzae isolates from patients with bacterial pneumonia were assessed. The CAP hospitalisation rate per 1000 child-years was 17.7, 14.3 and 9.7 in children aged <5 years and 1.18, 2.64 and 0.69 in children aged 5–15 years in 2008, 2012 and 2018, respectively. There was a 45% and 41% reduction in CAP hospitalisation rates, between the pre-PCV7 and PCV13 periods, respectively. Significant reductions occurred in the proportion of CAP due to PP and PCV13 serotypes. Conversely, no change occurred in the proportion of CAP caused by H. influenzae. The incidence of hospitalised CAP in children aged ⩽15 years was significantly reduced after the introduction of PCV13 in Japan. Continuous surveillance is necessary to detect emerging PP serotypes.

This paper applies a scenario planning approach, to outline some current uncertainties related to COVID-19 and what they might mean for plausible futures for which we should prepare, and to identify factors that we as individual faculty members and university institutions should be considering now, when planning for the future under COVID-19. Although the contextual focus of this paper is Canada, the content is likely applicable to other places where the COVID-19 epidemic curve is in its initial rising stage, and where universities are predominantly publicly funded institutions.

In foodborne outbreak investigations, case-control and cohort studies are used to test hypotheses and identify a source, but these studies are resource-intensive and may have challenges of representativeness, temporality or accessibility. We used online surveys to collect population control data for two foodborne outbreaks and compared the data collected to our cases and existing population exposure data. Online survey population controls were comparable to cases based on age and sex. Exposure data collected through online surveys were more precise than existing control data, represented the disease-specific exposure period and could be easily modified. In one outbreak the online control exposure data differed from established population data. In both outbreaks, the information from the online population control survey supported the hypothesis of the investigation. Our findings demonstrate that online surveys were a rapid and representative way to collect responses from controls during outbreak investigations.

Coronavirus disease 2019 (COVID-19) patients were classified into four clinical stages (uncomplicated illness, mild, severe and critical pneumonia) depending on disease severity. We aim to investigate the corresponding clinical, radiological and laboratory characteristics between different clinical stages. A retrospective, single-centre study of 101 confirmed patients with COVID-19 at Renmin Hospital of Wuhan University from 2 January to 28 January 2020 was enrolled; follow-up endpoint was on 8 February 2020. Clinical data were collected and compared during the course of illness. The median age of the 101 patients was 51.0 years and 33.6% were medical staff. Fever (68%), cough (50%) and fatigue (23%) are the most common symptoms. About 26% patients underwent the mechanical ventilation and 98% patients were treated with antibiotics. Thirty-seven per cent patients were cured and 11 died. On admission, the number of patients with uncomplicated illness, mild, severe and critical pneumonia were 2 [2%], 86 [85%], 11 [11%] and 2 [2%]. Forty-four of the 86 mild pneumonia progressed to severe illness within 4 days, with nine patients worsened due to critical pneumonia within 4 days. Two of the 11 severe patients improved to mild condition while three others deteriorated. Significant differences were observed among groups of different clinical stages in numbers of influenced pulmonary segments (6 vs. 12 vs. 17, P < 0.001). A significantly upward trend was witnessed in ground-glass opacities overlapped with striped shadows (33% vs. 42% vs. 55% vs. 80%, P < 0.001), while pure ground-glass opacities gradually decreased as disease progressed (45% vs. 35% vs. 24% vs. 13%, P < 0.001) within 12 days. Lymphocytes, prealbumin and albumin showed a downtrend as disease progressed from mild to severe or critical condition, an uptrend was found in white blood cells, C-reactive protein, neutrophils and lactate dehydrogenase. The proportions of serum amyloid A > 300 mg/l in mild, severe and critical conditions were 18%, 46% and 71%, respectively.

While predicting the course of an epidemic is difficult, predicting the course of a pandemic from an emerging virus is even more so. The validity of most predictive models relies on numerous parameters, involving biological and social characteristics often unknown or highly uncertain. Data of the COVID-19 epidemics in China, Japan, South Korea and Italy were used to build up deterministic models without strong assumptions. These models were then applied to other countries to identify the closest scenarios in order to foresee their coming behaviour. The models enabled to predict situations that were confirmed little by little, proving that these tools can be efficient and useful for decision making in a quickly evolving operational context.

The first case of 2019-nCoV pneumonia infection occurred in Wuhan, Hubei Province, South China Seafood Market in December 2019. As a group with a high probability of infection, health workers are faced with a certain degree of psychological challenges in the process of facing the epidemic. This study attempts to evaluate the impact of 2019-nCoV outbreak on the psychological state of Chinese health workers and to explore the influencing factors. During the period from 31 January 2020 to 4 February 2020, the ‘Questionnaire Star’ electronic questionnaire system was used to collect data. The 2019-nCoV impact questionnaire and The Impact of Event Scale (IES) were used to check the psychological status of health workers in China. A total of 442 valid data were collected in this study. Seventy-four (16.7%) male and 368 (83.3%) female individuals participated in this study. The average score of high arousal dimension was 5.15 (s.d. = 4.71), and the median score was 4.0 (IQR 2.0, 7.0). The average score of IES was 15.26 (s.d. = 11.23), and the median score was 13.5 (IQR 7.0, 21.0). Multiple regression analysis showed that there were critical statistical differences in high arousal scores among different gender groups (male 3.0 vs. female 5.0, P = 0.075). Whether being quarantined had significant statistical differences of IES scores (being quarantined 16.0 vs. not being quarantined 13.0, P = 0.021). The overall impact of the 2019-nCoV outbreak on health workers is at a mild level. Chinese health workers have good psychological coping ability in the face of public health emergencies.

Back-projection is an epidemiological analysis method that was developed to estimate HIV incidence using surveillance data on AIDS diagnoses. It was used extensively during the 1990s for this purpose as well as in other epidemiological contexts. Surveillance data on COVID-19 diagnoses can be analysed by the method of back-projection using information about the probability distribution of the time between infection and diagnosis, which is primarily determined by the incubation period. This paper demonstrates the value of such analyses using daily diagnoses from Australia. It is shown how back-projection can be used to assess the pattern of COVID-19 infection incidence over time and to assess the impact of control measures by investigating their temporal association with changes in incidence patterns. For Australia, these analyses reveal that peak infection incidence coincided with the introduction of border closures and social distancing restrictions, while the introduction of subsequent social distancing measures coincided with a continuing decline in incidence to very low levels. These associations were not directly discernible from the daily diagnosis counts, which continued to increase after the first stage of control measures. It is estimated that a one week delay in peak incidence would have led to a fivefold increase in total infections. Furthermore, at the height of the outbreak, half to three-quarters of all infections remained undiagnosed. Automated data analytics of routinely collected surveillance data are a valuable monitoring tool for the COVID-19 pandemic and may be useful for calibrating transmission dynamics models.

The coronavirus disease 2019 (COVID-19) outbreak caused by the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2 virus) has been sustained in China since December 2019, and has become a pandemic. The mental health of frontline medical staff is a concern. In this study, we aimed to identify the factors influencing medical worker anxiety in China during the COVID-19 outbreak. We conducted a cross-sectional study to estimate the prevalence of anxiety among medical staff in China from 10 February 2020 to 20 February 2020 using the Zung Self-rating Anxiety Scale (SAS) to assess anxiety, with the criteria of normal (⩽49), mild (50–59), moderate (60–70) and severe anxiety (⩾70). We used multivariable linear regression to determine the factors (e.g. having direct contact when treating infected patients, being a medical staff worker from Hubei province, being a suspect case) for anxiety. We also used adjusted models to confirm independent factors for anxiety after adjusting for gender, age, education and marital status. Of 512 medical staff in China, 164 (32.03%) had had direct contact treating infected patients. The prevalence of anxiety was 12.5%, with 53 workers suffering from mild (10.35%), seven workers suffering from moderate (1.36%) and four workers suffering from severe anxiety (0.78%). After adjusting for sociodemographic characteristics (gender, age, education and marital status), medical staff who had had direct contact treating infected patients experienced higher anxiety scores than those who had not had direct contact (β value = 2.33, confidence interval (CI) 0.65–4.00; P = 0.0068). A similar trend was observed in medical staff from Hubei province, compared with those from other parts of China (β value = 3.67, CI 1.44–5.89; P = 0.0013). The most important variable was suspect cases with high anxiety scores, compared to non-suspect cases (β value = 4.44, CI 1.55–7.33; P = 0.0028). In this survey of hospital medical workers during the COVID-19 outbreak in China, we found that study participants experienced anxiety symptoms, especially those who had direct clinical contact with infected patients; as did those in the worst affected areas, including Hubei province; and those who were suspect cases. Governments and healthcare authorities should proactively implement appropriate psychological intervention programmes, to prevent, alleviate or treat increased anxiety.

In late December 2019, patients of atypical pneumonia due to an unidentified microbial agent were reported in Wuhan, Hubei Province, China. Subsequently, a novel coronavirus was identified as the causative pathogen which was named SARS-CoV-2. As of 12 February 2020, more than 44 000 cases of SARS-CoV-2 infection have been confirmed in China and continue to expand. Provinces, municipalities and autonomous regions of China have launched first-level response to major public health emergencies one after another from 23 January 2020, which means restricting movement of people among provinces, municipalities and autonomous regions. The aim of this study was to explore the correlation between the migration scale index and the number of confirmed coronavirus disease 2019 (COVID-19) cases and to depict the effect of restricting population movement. In this study, Excel 2010 was used to demonstrate the temporal distribution at the day level and SPSS 23.0 was used to analyse the correlation between the migration scale index and the number of confirmed COVID-19 cases. We found that since 23 January 2020, Wuhan migration scale index has dropped significantly and since 26 January 2020, Hubei province migration scale index has dropped significantly. New confirmed COVID-19 cases per day in China except for Wuhan gradually increased since 24 January 2020, and showed a downward trend from 6 February 2020. New confirmed COVID-19 cases per day in China except for Hubei province gradually increased since 24 January 2020, and maintained at a high level from 24 January 2020 to 4 February 2020, then showed a downward trend. Wuhan migration scale index from 9 January to 22 January, 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Wuhan from 22 January to 4 February. Hubei province migration scale index from 10 January to 23 January and 11 January to 24 January was correlated with the number of new confirmed COVID-19 cases per day in China except for Hubei province from 22 January to 4 February. Our findings suggested that people who left Wuhan from 9 January to 22 January, and those who left Hubei province from 10 January to 24 January, led to the outbreak in the rest of China. The ‘Wuhan lockdown’ and the launching of the first-level response to this major public health emergency may have had a good effect on controlling the COVID-19 epidemic. Although new COVID-19 cases continued to be confirmed in China outside Wuhan and Hubei provinces, in our opinion, these are second-generation cases.

Salmonella is a leading cause of foodborne outbreaks in Taiwan. On 27 April 2018, a salmonellosis outbreak among customers of a restaurant was reported to the Taiwan CDC. We investigated the outbreak to identify infection sources and prevent further transmission. We interviewed ill customers and their dining companions. We conducted a case-control study to identify foods associated with the illness. Case-patients were those who had diarrhoea within 72 h after eating at the restaurant during 16–27 April 2018. Specimens, food samples and environmental samples were collected and tested for enteric pathogens. Salmonella isolates were analysed with pulse-field gel electrophoresis and whole-genome sequencing. We inspected the restaurant sanitation and reviewed kitchen surveillance camera recordings. We identified 47 case-patients, including one decedent. Compared with 44 controls, case-patients were more likely to have had a French toast sandwich (OR: 102.4; 95% CI: 18.7–952.3). Salmonella Enteritidis isolates from 16 case-patients shared an indistinguishable genotype. Camera recordings revealed eggshell contamination, long holding time at room temperature and use of leftovers during implicated food preparation. Recommendations for restaurant egg-containing food preparation are to use pasteurised egg products and ensure a high enough cooking temperature and long enough cooking time to prevent Salmonella contamination.