Inappropriate antibiotic use is a key driver of antibiotic resistance and one that can be mitigated through stewardship. A better understanding of current prescribing practices is needed to develop successful stewardship efforts. This study aims to identify factors that are associated with human cases of enteric illness receiving an antibiotic prescription. Cases of laboratory-confirmed enteric illness reported to the FoodNet Canada surveillance system between 2015 and 2019 were the subjects of this study. Laboratory data were combined with self-reported data collected from an enhanced case questionnaire that included demographic data, illness duration and symptoms, and antibiotic prescribing. The data were used to build univariable logistic regression models and a multivariable logistic regression model to explore what factors were associated with a case receiving an antibiotic prescription. The final multivariable model identified several factors as being significantly associated with cases being prescribed an antibiotic. Some of the identified associations indicate that current antibiotic prescribing practices include a substantial level of inappropriate use. This study provides evidence that antibiotic stewardship initiatives targeting infectious diarrhoea are needed to optimize antibiotic use and combat the rise of antibiotic resistance.

Since 1993, reports on tuberculosis (TB) outbreaks have been collected in Japan; however, there has never been an overall analysis of these TB outbreaks. We aim to provide one here. The TB outbreak data were obtained from the Ministry of Health, Labour and Welfare and are described in terms of time, place and transmission site. The average number of TB cases and latent tuberculosis infection (LTBI) were compared by the transmission site. Some 605 TB outbreaks with 3491 TB cases were reported in 1993–2015 with an increasing trend (r = 0.45), during which time 728 777 TB cases were reported nationwide. On an average, TB outbreaks occurred more often in April to May (5.5 outbreaks per 2 months) than in December to January (3.4). The most common transmission sites were workplaces (n = 255), followed by health facilities (n = 144), schools (n = 60) and welfare facilities (n = 48). Psychiatric hospitals and nursing homes had the highest average number of TB cases per outbreak (8.5 each), whereas schools and prisons had the highest numbers of LTBI cases (29.1 and 38.9, respectively). Countries, particularly those that have resources to investigate TB outbreaks, should collect and analyse findings of TB outbreaks, as it informs surveillance systems and eventually strengthens general health systems.

Global Health Security Index (GHSI) and Joint External Evaluation (JEE) are two well-known health security and related capability indices. We hypothesised that countries with higher GHSI or JEE scores would have detected their first COVID-19 case earlier, and would experience lower mortality outcome compared to countries with lower scores. We evaluated the effectiveness of GHSI and JEE in predicting countries' COVID-19 detection response times and mortality outcome (deaths/million). We used two different outcomes for the evaluation: (i) detection response time, the duration of time to the first confirmed case detection (from 31st December 2019 to 20th February 2020 when every country's first case was linked to travel from China) and (ii) mortality outcome (deaths/million) until 11th March and 1st July 2020, respectively. We interpreted the detection response time alongside previously published relative risk of the importation of COVID-19 cases from China. We performed multiple linear regression and negative binomial regression analysis to evaluate how these indices predicted the actual outcome. The two indices, GHSI and JEE were strongly correlated (r = 0.82), indicating a good agreement between them. However, both GHSI (r = 0.31) and JEE (r = 0.37) had a poor correlation with countries' COVID-19–related mortality outcome. Higher risk of importation of COVID-19 from China for a given country was negatively correlated with the time taken to detect the first case in that country (adjusted R2 = 0.63–0.66), while the GHSI and JEE had minimal predictive value. In the negative binomial regression model, countries' mortality outcome was strongly predicted by the percentage of the population aged 65 and above (incidence rate ratio (IRR): 1.10 (95% confidence interval (CI): 1.01–1.21) while overall GHSI score (IRR: 1.01 (95% CI: 0.98–1.01)) and JEE (IRR: 0.99 (95% CI: 0.96–1.02)) were not significant predictors. GHSI and JEE had lower predictive value for detection response time and mortality outcome due to COVID-19. We suggest introduction of a population healthiness parameter, to address demographic and comorbidity vulnerabilities, and reappraisal of the ranking system and methods used to obtain the index based on experience gained from this pandemic.

Clusters of Salmonella Enteritidis cases were identified by the Minnesota Department of Health using both pulsed-field gel electrophoresis (PFGE) and whole genome sequencing (WGS) single nucleotide polymorphism analysis from 1 January 2015 through 31 December 2017. The median turnaround time for obtaining WGS results was 11 days longer than for PFGE (12 vs. 1 day). WGS analysis more than doubled the number of clusters compared to PFGE analysis, but reduced the total number of cases included in clusters by 34%. The median cluster size was two cases for WGS compared to four for PFGE, and the median duration of WGS clusters was 27 days shorter than PFGE clusters. While the percentage of PFGE clusters with a confirmed source (46%) was higher than WGS clusters (32%), a higher percentage of cases in clusters that were confirmed as outbreaks reported the vehicle or exposure of interest for WGS (78%) than PFGE (46%). WGS cluster size was a significant predictor of an outbreak source being confirmed. WGS data have enhanced S. Enteritidis cluster investigations in Minnesota by improving the specificity of cluster case definitions and has become an integral part of the S. Enteritidis surveillance process.

Surveillance for acute flaccid paralysis (AFP) cases are essential for polio eradication. However, as most poliovirus infections are asymptomatic and some regions of the world are inaccessible, additional surveillance tools require development. Within England and Wales, we demonstrate how inclusion of environmental sampling (ENV) improves the sensitivity of detecting both wild and vaccine-derived polioviruses (VDPVs) when compared to current surveillance. Statistical modelling was used to estimate the spatial risk of wild and VDPV importation and circulation in England and Wales. We estimate the sensitivity of each surveillance mode to detect poliovirus and the probability of being free from poliovirus, defined as being below a pre-specified prevalence of infection. Poliovirus risk was higher within local authorities in Manchester, Birmingham, Bradford and London. The sensitivity of detecting wild poliovirus within a given month using AFP and enterovirus surveillance was estimated to be 0.096 (95% CI 0.055–0.134). Inclusion of ENV in the three highest risk local authorities and a site in London increased surveillance sensitivity to 0.192 (95% CI 0.191–0.193). The sensitivity of ENV strategies can be compared using the framework by varying sites and the frequency of sampling. The probability of being free from poliovirus slowly increased from the date of the last case in 1993. ENV within areas thought to have the highest risk improves detection of poliovirus, and has the potential to improve confidence in the polio-free status of England and Wales and detect VDPVs.

Among the different existing types of bacterial meningitis, the one caused by Neisseria meningitidis is the main presentation of invasive meningococcal disease (IMD). IMD is a significant public health concern and has a reported incidence rate in Argentina of 0.44 cases per 100 000 inhabitants in 2015. However, the actual incidence is thought to be higher as passive surveillance systems neither report nor identify 100% of all cases. The aim of this study is to develop an estimation of the burden of IMD in Argentina closer to reality by adjusting/correcting several limitations observed in the surveillance data available. A retrospective observational study has been performed using four Argentinean national databases recording the number of IMD cases and deaths, serogroups of N. meningitidis and ages, between 2007 to 2016. The reported data were adjusted to account for underreporting and to also integrate the cases missed due to well-known limitations associated with the diagnosis of N. meningitidis detection methods. Data were further analysed by serogroups of N. meningitidis and by age groups. After these adjustments, the potential numbers of IMD cases and IMD-related deaths are estimated to be 3.1 and 1.9 higher than reported, respectively. The study corrects the previous underestimation of the disease burden and provides expectedly more robust estimates aligned with international evidence and highlights the importance of active surveillance, with high-quality methods, for a better definition of preventive strategies against IMD in Argentina.

We studied trends in the incidence of health care-associated infections (HAIs) in LTCFs between 2009 and 2015 and determined the effect of participation in our network. Elder-care physicians reported weekly the number of cases of influenza-like illness, gastroenteritis, (probable) pneumonia, urinary tract infections (UTIs) and all-cause mortality. Trends in the incidence of infection and mortality in relation to LTCF characteristics were calculated using multilevel univariate and multivariate logistic regression. Thirty LTCF participated for 3 years or more, 16 for 2 years and the remaining 12 LTCF for 1 year. During the study period, the median number of beds decreased from 158 to 139, whereas the percentage of residents with private bedrooms increased from 14% to 87%. UTIs were the most frequently reported infections, followed by (probable) pneumonia and gastroenteritis. Adjusted for calendar year and season, we observed a statistically significant decrease in the incidence of influenza-like illness (odds ratio (OR) = 0.8, P < 0.01) and (probable) pneumonia (OR = 0.8, P < 0.01) for each extra year an LTCF participated. Although there are other likely contributors, such as more private rooms and enhanced infection control measures, the decreasing trend of HAI in LTCFs participating in surveillance implies that surveillance is a valuable addition to current strategies to optimise infection control.

The spread of the Zika virus (ZIKV) in the Americas led to large outbreaks across the region and most of the Southern hemisphere. Of greatest concern were complications following acute infection during pregnancy. At the beginning of the outbreak, the risk to unborn babies and their clinical presentation was unclear. This report describes the methods and results of the UK surveillance response to assess the risk of ZIKV to children born to returning travellers. Established surveillance systems operating within the UK – the paediatric and obstetric surveillance units for rare diseases, and national laboratory monitoring – enabled rapid assessment of this emerging public health threat. A combined total of 11 women experiencing adverse pregnancy outcomes after possible ZIKV exposure were reported by the three surveillance systems; five miscarriages, two intrauterine deaths and four children with clinical presentations potentially associated with ZIKV infection. Sixteen women were diagnosed with ZIKV during pregnancy in the UK. Amongst the offspring of these women, there was unequivocal laboratory evidence of infection in only one child. In the UK, the number and risk of congenital ZIKV infection for travellers returning from ZIKV-affected countries is very small.

Norovirus is a predominant cause of infectious gastroenteritis in countries worldwide [1–5]. It accounts for approximately 50% of acute gastroenteritis (AGE) and >90% of viral gastroenteritis outbreaks [6, 7]. The incubation period ranges between 10 and 48 h and illness duration is generally 1–3 days with self-limiting symptoms; however, this duration is often longer (e.g. 4–6 days) in vulnerable populations such as hospital patients or young children [2, 8]. Symptomatic infection of norovirus presents as acute vomiting, diarrhoea, abdominal cramps and nausea, with severe vomiting and diarrhoea (non-bloody) being most common [2, 5, 9].

In Sierra Leone, the Ebola virus disease (EVD) outbreak occurred with substantial differences between districts with someone even not affected. To monitor the epidemic, a community event-based surveillance system was set up, collecting data into the Viral Haemorrhagic Fever (VHF) database. We analysed the VHF database of Tonkolili district to describe the epidemiology of the EVD outbreak during July 2014–June 2015 (data availability). Multivariable analysis was used to identify risk factors for EVD, fatal EVD and barriers to healthcare access, by comparing EVD-positive vs. EVD-negative cases. Key-performance indicators for EVD response were also measured. Overall, 454 EVD-positive cases were reported. At multivariable analysis, the odds of EVD was higher among those reporting contacts with an EVD-positive/suspected case (odds ratio (OR) 2.47; 95% confidence interval (CI) 2.44–2.50; P < 0.01) and those attending funeral (OR 1.02; 95% CI 1.01–1.04; P < 0.01). EVD cases from Kunike chiefdom had a lower odds of death (OR 0.22; 95% CI 0.08–0.44; P < 0.01) and were also more likely to be hospitalised (OR 2.34; 95% CI 1.23–4.57; P < 0.05). Only 25.1% of alerts were generated within 1 day from symptom onset. EVD preparedness and response plans for Tonkolili should include social-mobilisation activities targeting Ebola/knowledge-attitudes-practice during funeral attendance, to avoid contact with suspected cases and to increase awareness on EVD symptoms, in order to reduce delays between symptom onset to alert generation and consequently improve the outbreak-response promptness.

To determine the burden of skin and soft tissue infections (SSTI), the nature of antimicrobial prescribing and factors contributing to inappropriate prescribing for SSTIs in Australian aged care facilities, SSTI and antimicrobial prescribing data were collected via a standardised national survey. The proportion of residents prescribed ⩾1 antimicrobial for presumed SSTI and the proportion whose infections met McGeer et al. surveillance definitions were determined. Antimicrobial choice was compared to national prescribing guidelines and prescription duration analysed using a negative binomial mixed-effects regression model. Of 12 319 surveyed residents, 452 (3.7%) were prescribed an antimicrobial for a SSTI and 29% of these residents had confirmed infection. Topical clotrimazole was most frequently prescribed, often for unspecified indications. Where an indication was documented, antimicrobial choice was generally aligned with recommendations. Duration of prescribing (in days) was associated with use of an agent for prophylaxis (rate ratio (RR) 1.63, 95% confidence interval (CI) 1.08–2.52), PRN orders (RR 2.10, 95% CI 1.42–3.11) and prescription of a topical agent (RR 1.47, 95% CI 1.08–2.02), while documentation of a review or stop date was associated with reduced duration of prescribing (RR 0.33, 95% CI 0.25–0.43). Antimicrobial prescribing for SSTI is frequent in aged care facilities in Australia. Methods to enhance appropriate prescribing, including clinician documentation, are required.

Austerity might have affected the capacity of public hospitals in Greece to diagnose salmonellosis (laboratory capacity) over the period 2010–2016, as well as the performance of the existing surveillance systems. The scope of this paper is to present data on laboratory capacity over these years, as well as the results of a two-source capture-recapture study (data from Mandatory Notification System and National Reference Laboratory System for Salmonella). The main findings were that: (a) laboratory capacity was high and steady besides the financial crisis, (b) the estimated number of laboratory-confirmed cases (n = 6017, 95% CI 5892–6142) resulted in an incidence rate (7.9 cases/100 000 population) almost twice than that reported by the two systems Mandatory Notification System (MNS); 4.1 and National Reference Laboratory System (NRLS); 4.5 cases/100 000 population, (c) underreporting was high for both systems (MNS; 47.5% and NRLS; 42.8%) and (d) differences by geographical region, size and type of hospital were identified. We suggest that (a) specific interventions are needed to increase completeness of the systems by type of hospital and geographical region, (b) record linkage can help in estimating the disease burden in a more valid way than each system separately and (c) a common electronic database in order to feed one system to the other could significantly increase completeness of both systems.

We evaluated and compared the completeness, timeliness, simplicity, usefulness and flexibility between the former National Tuberculosis (TB) Surveillance System (NTBSS) and the newer Computerised Infectious Disease Reporting System (CIDR). Completeness was assessed by examining the field completion of key variables and median time from diagnosis to notification was calculated to evaluate timeliness. Differences between the two systems on completeness and timeliness were statistically assessed using χ2 and Wilcoxon rank-sum test, respectively. An online questionnaire on simplicity, flexibility and usefulness was sent to key stakeholders. Time and diagnosis-related variables were more complete in NTBSS, while variables on drug susceptibility, HIV and laboratory tests were more complete in CIDR (P < 0.05). The median time notification interval increased significantly in CIDR (P < 0.05). Stakeholders thought that CIDR is simpler (37.5%), more useful (41.7%) and more flexible (29.2%) than NTBSS. This study demonstrated that CIDR did not improve data completeness and decreased timeliness of notification. Simplicity, usefulness and flexibility were improved but qualitative methods should be applied to further explore these results.

This study aimed at evaluating the integrated measles and rubella surveillance system (IMRSS) in Apulia region, Italy, from its introduction in 2013 to 30 June 2016. Measles and rubella case reports were extracted from IMRSS. We estimated system sensitivity at the level of case reporting, using the capture–recapture method for three data sources. Data quality was described as the completeness of variables and timeliness of notification as the median-time interval from symptoms onset to initial alert. The proportion of suspected cases with laboratory investigation, the rate of discarded cases and the origin of infection were also computed. A total of 127 measles and four rubella suspected cases were reported to IMRSS and 82 were laboratory confirmed. Focusing our analysis on measles, IMRSS sensitivity was 82% (95% CI: 75–87). Completeness was >98% for mandatory variables and 57% for ‘genotyping’. The median-time interval from symptoms onset to initial alert was 4.5 days, with a timeliness of notification of 33% (41 cases reported ⩽48 h). The proportion of laboratory investigation was 87%. The rate of discarded cases was 0.1 per 100 000 inhabitants per year. The origin of infection was identified for 85% of cases. It is concluded that IMRSS provides good quality data and has good sensitivity; still efforts should be made to improve the completeness of laboratory-related variables, timeliness and to increase the rate of discarded cases.

Acute rheumatic fever (ARF) continues to produce a significant burden of disease in New Zealand (NZ) Māori and Pacific peoples. Serious limitations in national surveillance data mean that accurate case totals cannot be generated. Given the changing epidemiology of ARF in NZ and the major national rheumatic fever prevention programme (2012–2017), we updated our previous likely true case number estimates using capture–recapture analyses. Aims were to estimate the likely true incidence of ARF in NZ and comment on the changing ability to detect cases. Data were obtained from national hospitalisation and notification databases. The Chapman Estimate partially adjusted for bias. An estimated 2342 likely true new cases arose from 1997 to 2015, giving a mean annual incidence of 2·9 per 100 000 (95% CI 2·5–3·5). Compared with the pre-intervention (2009–2011) baseline incidence (3·4 per 100 000, 95% CI 2·9–4·0), the likely true 2015 incidence declined 44%. Large gaps in data completeness are slowly closing. During the period 2012–2015, 723 cases were identified; 83·8% of notifications were matched to hospitalisation data, and 87·2% of hospitalisations matched to notifications. Despite this improvement, clinicians need to remain aware of the need to notify atypical patients. A possible unintended consequence of the national ARF prevention programme is increased misdiagnosis.

Influenza epidemics are monitored using influenza-like illness (ILI) data reported by health-care professionals. Timely detection of the onset of epidemics is often performed by applying a statistical method on weekly ILI incidence estimates with a large range of methods used worldwide. However, performance evaluation and comparison of these algorithms is hindered by: (1) the absence of a gold standard regarding influenza epidemic periods and (2) the absence of consensual evaluation criteria. As of now, performance evaluations metrics are based only on sensitivity, specificity and timeliness of detection, since definitions are not clear for time-repeated measurements such as weekly epidemic detection. We aimed to evaluate several epidemic detection methods by comparing their alerts to a gold standard determined by international expert consensus. We introduced new performance metrics that meet important objective of influenza surveillance in temperate countries: to detect accurately the start of the single epidemic period each year. Evaluations are presented using ILI incidence in France between 1995 and 2011. We found that the two performance metrics defined allowed discrimination between epidemic detection methods. In the context of performance detection evaluation, other metrics used commonly than the standard could better achieve the needs of real-time influenza surveillance.