Routine Surveillance Data Research Articles

A recent history of disease outbreaks in Kenya, 2007–2022: Findings from routine surveillance data

BackgroundAfrica reports the highest number of outbreaks globally, accounting for 39% of all outbreaks in 2022. The Integrated Disease Surveillance and Response strategy in Kenya ensures the reporting of outbreaks up to the national level. We present a summary of the burden of reported disease outbreaks in Kenya, 2007–2022.MethodsWe reviewed historical surveillance data, 2007–2022, summarized the annual caseload and deaths of reported outbreaks, and classified the outbreaks into 3 categories, that is high, moderate, and low burden. A nested Poisson regression model was fit to determine whether there was a significant increase in the number of diseases and counties reporting outbreaks over time.ResultsTwenty-three diseases were reported. COVID-19, cholera, epidemic malaria, kala-azar, and measles were associated with a high disease burden. The highest number of diseases reported in a single year was 10. We observed an increase in the number of outbreaks over time (IRR = 1.26, 95% CI [1.22–1.29], p < 0.001), and an increase in the number of counties reporting outbreaks over time (r = 0.97, p < 0.001).ConclusionThere was an increase in the frequency and geographic occurrence of outbreaks. The differences in outbreak occurrence between counties necessitate targeted and enhanced preventive, preparedness, and response interventions at the sub-national level to reduce the burden of outbreaks.

The impact of the RTS,S malaria vaccine on uncomplicated malaria: evidence from the phase IV study districts, Upper East Region, Ghana, 2020–2022

BackgroundThe RTS,S malaria vaccine has been prequalified for use in endemic settings prioritizing areas with moderate to high disease transmission. The impact of a vaccine at the population level may differ from observations during clinical trial due to programmatic, and individual-related factors, among others. The objective of this study was to assess the impact of the RTS,S malaria vaccine on uncomplicated malaria among children aged 12–59 months in the Phase IV study districts, Upper East Region, Ghana.MethodsA retrospective study was conducted using routine malaria surveillance data for the period 2020–2022. The burden of uncomplicated malaria was compared between the implementing (Kasena Nankana East and West districts) and comparator areas (Builsa North and South districts). The impact of RTS,S malaria vaccine was assessed by estimating the percentage reduction in uncomplicated malaria and incidence averted in the implementing area, accounting for the effect of confounders.ResultsOver 50,000 episodes of uncomplicated malaria among children aged 12–59 months were included in the study. Uncomplicated malaria was reduced by 33% (95%CI 29–36) over the entire study period, but the malaria incidence averted declined from 324/1,000 (95% CI 298–339; p < 0.0001) in 2020 to 287/1000 (95% CI 274–299; p < 0.0001) in 2022.ConclusionThe RTS,S malaria vaccine significantly reduced the burden of uncomplicated malaria among children aged 12–59 months in the implementing area. The sequential marginal declines in malaria incidence averted over the study period might be due to waning of protective immunity and acquisition of natural immunity as children age. Strengthening uptake of the currently recommended vaccines and other malaria control interventions is required to improve public health impact.

A Statistical Model for Inference of Recent and Incident HIV Infection Using Surveillance Data on Individuals Newly Diagnosed With HIV Infection in Scotland

Background: To inform global ambitions to end AIDS, evaluation of progress toward HIV incidence reduction requires robust methods to measure incidence. Although HIV diagnosis date in routine HIV/AIDS surveillance systems are often used as a surrogate marker for incidence, it can be misleading if acquisition of transmission occurred years before testing. Other information present in data such as antibody testing dates, avidity testing result, and CD4 counts can assist, but the degree of missing data is often prohibitive. Methods: We constructed a Bayesian statistical model to estimate the annual proportion of first ever HIV diagnoses in Scotland (period 2015–2019) that represent recent HIV infection (ie, occurring within the previous 3–4 months) and incident HIV infection (ie, infection within the previous 12 months), by synthesizing avidity testing results and surveillance data on the interval since last negative HIV test. Results: Over the 5-year analysis period, the model-estimated proportion of incident infection was 43.9% (95% CI: 40.9 to 47.0), and the proportion of recent HIV infection was 21.6% (95% CI: 19.1 to 24.1). Among the mode of HIV acquisition categories, the highest proportion of recent infection was estimated for people who inject drugs: 27.4% (95% CI: 20.4 to 34.4). Conclusions: The Bayesian approach is appropriate for the high prevalence of missing data that can occur in routine surveillance data sets. The proposed model will aid countries in improving their understanding of the number of people who have recently acquired their infection, which is needed to progress toward the goal of HIV transmission elimination.

Results from a retrospective case finding and re-engagement exercise for people previously diagnosed with hepatitis C virus to increase uptake of directly acting antiviral treatment

BackgroundDirect acting antivirals (DAAs) for the Hepatitis C virus (HCV) have shifted the World Health Organisation global strategic focus to the elimination of HCV by 2030. In England, the UK Health Security Agency (UKHSA) led a national ‘patient re-engagement exercise’, using routine surveillance data, which was delivered through the HCV Operational Delivery Networks (ODNs) with support from National Health Service England (NHSE), to help find and support people with a positive HCV PCR test result to access treatment. We report a quantitative evaluation of outcomes of this exercise.MethodsIndividuals with a recorded positive HCV antibody or PCR result between 1996 and 2017 were identified using UKHSA’s records of HCV laboratory diagnosis. Linkage with established health-care datasets helped to enhance patient identification and minimise attempts to contact deceased or previously treated individuals. From September to November 2018 each ODN was provided with a local list of diagnosed individuals. ODNs were asked to perform further data quality checks through local systems and then write to each individual’s GP to inform them that the individual would be contacted by the ODN to offer confirmatory HCV PCR testing, assessment and treatment unless the GP advised otherwise. Outcomes of interest were receipt of treatment, a negative PCR result, and death. Data were collected in 2022.ResultsOf 176,555 individuals with a positive HCV laboratory report, 55,329 individuals were included in the exercise following linkage to healthcare datasets and data reconciliation. Participants in the study had a median age of 51 years (IQR: 43, 59), 36,779 (66.5%) were males, 47,668 (86.2%) were diagnosed before 2016 and 11,148 (20.2%) lived in London. Of the study population, 7,442 (13.4%) had evidence of treatment after the re-engagement exercise commenced, 6,435 (11.6%) were reported as PCR negative (96% had no previous treatment records), 4,195 (7.6%) had prescription data indicating treatment before the exercise commenced or were reported to have been treated previously by their ODN, and 2,990 (5.4%) had died. The status of 32,802 (59.3%) people remains unknown.ConclusionsA substantial number of those included had treatment recorded after the exercise commenced, however, many more remain unengaged. Evaluation of the exercise highlighted areas that could be streamlined to improve future exercises.

Drug-resistant tuberculosis care and treatment outcomes over the last 15 years in Ethiopia: Results from a mixed-method review of trends.

Drug resistant tuberculosis (DR-TB) remains a global challenge with about a third of the cases are not detected. With the recent advances in the diagnosis and treatment follow-up of DR-TB, there have been improvements with treatment success rates. However, there is limited evidence on the successful models of care that have consistently registered good outcomes. Our aim was to assess Ethiopia's experience in scaling up an ambulatory, decentralized model of care while managing multiple regimen transition processes and external shocks. This was a cross-sectional, mixed-method study. For the quantitative data, we reviewed routine surveillance data for the period 2009-2022 and collected additional data from publicly available reports. We then analyzed the data descriptively. Qualitative data were collected from program reports, quarterly presentations, minutes of technical working group meetings, and clinical review committee reports and analyzed thematically. The number of DR-TB treatment initiating centers increased from 1 to 67, and enrollment increased from 88 in 2010 to 741 in 2019, but declined to 518 in 2022. A treatment success rate (TSR) of over 70% was sustained. The decentralized and ambulatory service delivery remained the core service delivery model. The country successfully navigated multiple regimen transitions, including the recently introduced six-month short oral regimen. Several challenges remain, including the lack of strong and sustainable specimen transportation system, lack of established systems for timely tracing and linking of missed DR-TB cases, and data quality issues. Ethiopia scaled up a decentralized ambulatory model of care, kept up to date with recent developments in treatment regimens, and maintained a high TSR, despite the influence of multiple external challenges. The recent decline in case notification requires a deeper look into the underlying reasons. The feasibility of fully integrating DR-TB treatment and follow up at community level should be explored further.

Age-corrected development of preterm children: a population-based study.

The standard practice to account for expected developmental lags in preterm children is calculating their age as if born on their expected delivery date. We aimed to assess the accuracy of standard age correction in a large and diverse population. Routine surveillance data was extracted from a national network of mother-child clinics covering over 70% of the Israeli population. We included children with no developmental delay at age 2 years old, to exclude chronic dysfunctions. For each milestone assessed before age 2 years old we calculated the age of 90% and 95% population-milestone attainment, and compared attainment age between term and preterm children, before and after age correction. The study consisted of n = 656,986 and n = 52,662 term and preterm children respectively. Without age correction extensive gaps were observed in all domains, all degrees of prematurity and persisted throughout the first 2 years of life. With age correction most gaps were resolved among moderate/late preterm children, but not among extreme and very preterm, with residual gaps of at least 2 months for motor and 1 month for language-social development. While standard age correction accounts for maturational delay in late/moderate preterm children, it may underestimate the maturational delay among very/ extremely preterm children. Standard age correction is sufficient for late/moderate preterm children, and underestimates the maturational delay of extreme and very preterm children. Prior evidence on the accuracy of standard age correction across developmental domains and degrees of prematurity was limited to dated, small-scale data. Maturational delays persist throughout the first 2 years of life across all developmental domains and in all levels of prematurity. Developmental assessments without age correction may lead to unnecessary parental anxiety.

Predicting the incidence of rifampicin resistant tuberculosis in Yunnan, China: a seasonal time series analysis based on routine surveillance data

BackgroundRifampicin resistant tuberculosis (RR-TB) poses a growing threat to individuals and communities. This study utilized a seasonal autoregressive integrated moving average (SARIMA) model to quantitatively predict the monthly incidence of RR-TB in Yunnan Province which could guide government health administration departments and the centers for disease control and prevention (CDC) in preventing and controlling the RR-TB epidemic.MethodsThe study utilized routine surveillance reporting data from the infectious Disease Network Surveillance and Reporting System. Monthly incidence rates of RR-TB were collected from January 2019 to December 2022. A time series SARIMA model was used to predict the number of monthly RR-TB cases in Yunnan Province in 2023, and the model was validated using time series plots, seasonal and non-seasonal differencing, autocorrelation and partial autocorrelation analysis, and white noise tests.ResultsFrom 2019 to 2022, the incidence of RR-TB decreases as the incidence of all TB decreases (P < 0.05). There was no significant change in the proportion of RR-TB among all TB cases, which remained within 2.5% (P>0.05). The time series decomposition shows that it presented obvious seasonality, periodicity and randomness after being decomposed. Time series analysis was performed on the original series after 1 non-seasonal difference and 1 seasonal difference, the ADF test showed P < 0.05. According to ACF and PACF, the SARIMA (1, 1, 1) (1, 1, 0)12 model was chosen and statistically significant model parameter estimates (P < 0.05). The predicted seasonal trend of RR-TB incidence in 2019 to 2023 was similar to the actual data. The percentage accuracy in the prediction excesses 80% in 2019 to 2022 and is all within 95% CI. However there was a certain gap between the actual incidence and the predicted value in 2023, and the acutual incidence had increased by 12.4% compared to 2022. The percentage of accuracy in the prediction was only 70% in 2023.ConclusionsWe found the incidence of RR-TB was based on that of all TB in Yunnan. The SARIMA model successfully predicted the seasonal incidence trend of RR-TB in Yunnan Province in 2019 to 2023, but the prediction precision could be influenced by factors such as new infectious disease outbreaks or pandemics, social issues, environmental challenges or other unknown risks. Hence CDCs should pay special attention to the post epidemic effects of new infectious disease outbreaks or pandemics, carry out monitoring and early warning, and better optimize disease prediction models.

Estimation of COVID-19 vaccine effectiveness against infections and severe outcomes using routine surveillance data in Kosovo, July-September 2021.

COVID-19 vaccines have proven effective against severe outcomes in many settings, yet vaccine effectiveness (VE) estimates remain lacking for Kosovo. We aimed to estimate VE against COVID-19 infections, hospitalisations, and deaths for one and two vaccine doses during the fourth pandemic wave in July-September 2021, the period when vaccination initially became widely available. We analysed routine surveillance data to define cases and vaccination status as partially (one dose) or completely (two doses) vaccinated. We used the screening method to calculate the proportion of cases with the outcomes vaccinated (PCV). The proportion of the population vaccinated (PPV) was based on numbers vaccinated and the Kosovo population estimate on 30/09/2021. Between July-September 2021, 51,804 COVID-19 cases were reported in Kosovo with 9.3% of cases partially and 3.4% completely vaccinated. Estimated vaccine effectiveness for one dose was 93.1% (95%CI:92.9-93.2%) for infections, 90.3% (95%CI:88.8-91.7%) for hospitalisations, and 90.3% (95%CI:88.4-92.1%) for deaths. Estimated vaccine effectiveness for two doses was 97.8% (95%CI:97.6-97.9%) for infections, 94.5% (95%CI:93.3-95.6%) for hospitalisations, and 94.2% (95%CI: 93.7-96.5%) for deaths. This study provides real-world evidence for COVID-19 vaccine effectiveness in Kosovo using routine administrative data sources and the screening method. COVID-19 vaccine effectiveness against infections and severe outcomes in Kosovo was higher with two vaccine doses than one dose, which is in accordance with findings from other study designs and settings. Using the screening method in our study reflects an important initial methodology for estimating vaccine effectiveness with routine surveillance that may be particularly important for low- and middle-income settings with less robust surveillance systems or fewer opportunities to conduct more robust vaccine effectiveness study designs.

Clostridioides difficile infection following COVID-19: A nationwide analysis using routine surveillance data in Wales

CDI incidence has increased in Wales from summer 2020 and has remained elevated. There is evidence of poorer outcomes from concurrent CDI and COVID-19 infections, but it is not clear if infection with COVID-19 directly impacts likelihood of CDI infection. We investigated the relationship between CDI and COVID-19 and the impact of secondary infections. We conducted two analytical studies using routine surveillance data: i) population level ecological case control study comparing CDI cases in the Welsh population by SARS-COV-2 exposure in the previous 90 days, ii) cohort study of COVID-19 cases by secondary infection presence, investigating CDI development within 90 days. Case control: 12% (196/1645) of CDI cases had prior COVID-19 and were twice as likely to have had COVID-19 compared to general population controls, when controlling for other infection history (OR 2.1, CI 1.8-2.5, p<0.0001). CDI cases were 8 times more likely to have had other infections, independent of COVID-19 history (OR 8.0, CI 7.0-9.0, p<0.001). 2% (2,255/137,620)) of the COVID-19 cohort developed >1 secondary infection, and <1% (185/137620) developed CDI within 90 days. CDI risk was four times higher in those with secondary infections, after age and sex adjustment (RR 4.6, CI 3.1 - 6.1, p<0.001). CDI risk increased with age and did not differ by sex. Findings suggest a relationship between COVID-19 and CDI. However, incidence of CDI following COVID-19 was a rare outcome generally, suggesting other factors are likely contributing to the increased rates of CDI observed since 2020.

Fine-scale maps of malaria incidence to inform risk stratification in Laos

BackgroundMalaria risk maps are crucial for controlling and eliminating malaria by identifying areas of varying transmission risk. In the Greater Mekong Subregion, these maps guide interventions and resource allocation. This article focuses on analysing changes in malaria transmission and developing fine-scale risk maps using five years of routine surveillance data in Laos (2017–2021). The study employed data from 1160 geolocated health facilities in Laos, along with high-resolution environmental data.MethodsA Bayesian geostatistical framework incorporating population data and treatment-seeking propensity was developed. The models incorporated static and dynamic factors and accounted for spatial heterogeneity.ResultsResults showed a significant decline in malaria cases in Laos over the five-year period and a shift in transmission patterns. While the north became malaria-free, the south experienced ongoing transmission with sporadic outbreaks.ConclusionThe risk maps provided insights into changing transmission patterns and supported risk stratification. These risk maps are valuable tools for malaria control in Laos, aiding resource allocation, identifying intervention gaps, and raising public awareness. The study enhances understanding of malaria transmission dynamics and facilitates evidence-based decision-making for targeted interventions in high-risk areas.

Epidemiological characteristics and hospital outcomes of hospitalized Lassa fever cases during the 2022-2023 outbreak in Liberia

Background Lassa fever is an endemic and immediately notifiable disease in Liberia, and one laboratory confirmed case constitutes an outbreak. We described the epidemiological characteristics and hospital outcome of Lassa fever cases hospitalized during the 2022-2023 outbreak in Liberia. Methods A cohort study was conducted using routine Lassa fever surveillance data from the 2022-2023 outbreak in Liberia. Descriptive statistics were used to summarize the data and log binomial regression to assess the association between epidemiological characteristics and mortality. Results A total of 439 suspected Lassa fever cases were reported. The median age was 22 (interquartile range: 10-33) years and 233 (53%) were women. The median number of days between symptom onset and admission was 4 (IQR 2-7). Of the 439 cases, 416 (95%) were tested for Lassa fever and 138 were confirmed with 33% positivity rate. The majority, 290 (69%), of confirmed cases were &lt;30 years, 78 (57%) were females, and 81 (59%) were reported during the dry season (October – March). Contact with rodents, 94 (68%), was the commonest mode of exposure. Fever, 128 (93%), malaise, 121 (88%), headache, 114 (83%) and myalgia, 114 (83%) were the most common clinical characteristics. There were 83 (19%) deaths among hospitalized suspected Lassa fever cases - 42 deaths (15%) among 278 individuals who tested negative and 41 among confirmed cases with 30% case fatality rate (CFR). The highest CFR was recorded among those aged 40-49 years, 8 (67%) and those aged≥50, 5 (63%). There was no significant association between epidemiological characteristics and Lassa fever mortality. Conclusions The outbreak highlighted a high disease burden of Lassa fever with young adults disproportionately infected, and substantial mortality, even among those who tested negative for the virus. This underscores the urgent need for preventive measures like vaccines and health education campaigns.

CalScope: methodology and lessons learned for conducting a remote statewide SARS-CoV-2 seroprevalence study in California using an at-home dried blood spot collection kit and online survey.

To describe the methodology for conducting the CalScope study, a remote, population-based survey launched by the California Department of Public Health (CDPH) to estimate SARS-CoV-2 seroprevalence and understand COVID-19 disease burden in California. Between April 2021 and August 2022, 666,857 randomly selected households were invited by mail to complete an online survey and at-home test kit for up to one adult and one child. A gift card was given for each completed survey and test kit. Multiple customized REDCap databases were used to create a data system which provided task automation and scalable data management through API integrations. Support infrastructure was developed to manage follow-up for participant questions and a communications plan was used for outreach through local partners. Across 3 waves, 32,671 out of 666,857 (4.9%) households registered, 6.3% by phone using an interactive voice response (IVR) system and 95.7% in English. Overall, 25,488 (78.0%) households completed surveys, while 23,396 (71.6%) households returned blood samples for testing. Support requests (n = 5,807) received through the web-based form (36.3%), by email (34.1%), and voicemail (29.7%) were mostly concerned with the test kit (31.6%), test result (26.8%), and gift card (21.3%). Ensuring a well-integrated and scalable data system, responsive support infrastructure for participant follow-up, and appropriate academic and local health department partnerships for study management and communication allowed for successful rollout of a large population-based survey. Remote data collection utilizing online surveys and at-home test kits can complement routine surveillance data for a state health department.

Mixed-method evaluation study of a targeted mass drug administration of long-acting anti-malarials among children aged 3 months to 15 years in the Bossangoa sub-prefecture, Ouham, Central African Republic, during the COVID-19 pandemic

BackgroundIn 2020, during the COVID-19 pandemic, Médecins Sans Frontières (MSF) initiated three cycles of dihydroartemisin-piperaquine (DHA-PQ) mass drug administration (MDA) for children aged three months to 15 years within Bossangoa sub-prefecture, Central African Republic. Coverage, clinical impact, and community members perspectives were evaluated to inform the use of MDAs in humanitarian emergencies.MethodsA household survey was undertaken after the MDA focusing on participation, recent illness among eligible children, and household satisfaction. Using routine surveillance data, the reduction during the MDA period compared to the same period of preceding two years in consultations, malaria diagnoses, malaria rapid diagnostic test (RDT) positivity in three MSF community healthcare facilities (HFs), and the reduction in severe malaria admissions at the regional hospital were estimated. Twenty-seven focus groups discussions (FGDs) with community members were conducted.ResultsOverall coverage based on the MDA card or verbal report was 94.3% (95% confidence interval (CI): 86.3–97.8%). Among participants of the household survey, 2.6% (95% CI 1.6–40.3%) of round 3 MDA participants experienced illness in the preceding four weeks compared to 30.6% (95% CI 22.1–40.8%) of MDA non-participants. One community HF experienced a 54.5% (95% CI 50.8–57.9) reduction in consultations, a 73.7% (95% CI 70.5–76.5) reduction in malaria diagnoses, and 42.9% (95% CI 36.0–49.0) reduction in the proportion of positive RDTs among children under five. A second community HF experienced an increase in consultations (+ 15.1% (− 23.3 to 7.5)) and stable malaria diagnoses (4.2% (3.9–11.6)). A third community HF experienced an increase in consultations (+ 41.1% (95% CI 51.2–31.8) and malaria diagnoses (+ 37.3% (95% CI 47.4–27.9)). There were a 25.2% (95% CI 2.0–42.8) reduction in hospital admissions with severe malaria among children under five from the MDA area. FGDs revealed community members perceived less illness among children because of the MDA, as well as fewer hospitalizations. Other indirect benefits such as reduced household expenditure on healthcare were also described.ConclusionThe MDA achieved high coverage and community acceptance. While some positive health impact was observed, it was resource intensive, particularly in this rural context. The priority for malaria control in humanitarian contexts should remain diagnosis and treatment. MDA may be additional tool where the context supports its implementation.

Cohort profile: A population-based record linkage platform to address critical epidemiological evidence gaps in respiratory syncytial virus and other respiratory infections

IntroductionThe Western Australia (WA) Respiratory Infections Linked Data Platform is a population-based cohort established to investigate the epidemiology of RSV and other respiratory infections in children aged 0-10 years, incorporating microbiological testing patterns, hospital admissions, emergency department presentations, and socio-demographic data. MethodsThe cohort was formed through individual linkages between datasets from the WA Department of Health including the Birth and Death Registry, Midwives Notification System (MNS), Hospital Morbidity Data Collection, Emergency Department Data Collection, WA Notifiable Diseases Database, WA Register of Developmental Anomalies, WA Cerebral Palsy Register, WA Antenatal Vaccination Database, WA Family Connections, and PathWest Respiratory Virus Surveillance Data. Hospitalisations and emergency department presentations were temporally linked to routine respiratory viral surveillance data. ResultsThe cohort consists of 368,830 WA births between 1 January 2010 and 31 December 2020 with accompanying perinatal and demographic data, and with secondary care follow-up to 30 June 2022. Of these births, 24,660 (6.7%) identify as Aboriginal. A total of 4,077 (1.1%) children died from all causes during the study period (2010-2020), and 9.2% (33,818) of children were born preterm (&lt;37 weeks). ConclusionThe Respiratory Infections Linked Data Platform enables epidemiological investigations, identifying virus-specific risk groups, risk factors, clinical presentation, viral testing patterns, long-term impacts and accurate measures of viral incidence rates in risk and population sub-groups This will not only aid in the calculation of cost-effectiveness estimates of interventions such as immunisations, but also provide guidance for design and implementation of such programs to priority groups. The Respiratory Infections Linked Data Platform will also enable evaluation of the direct and indirect effects of maternal and infant vaccines and new therapeutics. Analyses using this platform will also generate epidemiological data needed for other respiratory viruses on the vaccine pipeline such as parainfluenza virus and human metapneumovirus.

Characterization of Antibiotic Resistance in Select Tertiary Hospitals in Uganda: An Evaluation of 2020 to 2023 Routine Surveillance Data.

Antimicrobial resistance (AMR) is a public health concern in Uganda. We sought to conduct an extended profiling of AMR burden at selected Ugandan tertiary hospitals. We analyzed routine surveillance data collected between October 2020 and March 2023 from 10 tertiary hospitals. The analysis was stratified according to the hospital unit, age, gender, specimen type, and time. Up to 2754 isolates were recovered, primarily from pus: 1443 (52.4%); urine: 1035 (37.6%); and blood: 245 (8.9%). Most pathogens were Staphylococcus aureus, 1020 (37%), Escherichia coli, 808 (29.3%), and Klebsiella spp., 200 (7.3%). Only 28% of Escherichia coli and 42% of the other Enterobacterales were susceptible to ceftriaxone, while only 44% of Staphylococcus aureus were susceptible to methicillin (56% were MRSA). Enterococcus spp. susceptibility to vancomycin was 72%. The 5-24-year-old had 8% lower ampicillin susceptibility than the >65-year-old, while the 25-44-year-old had 8% lower ciprofloxacin susceptibility than the >65-year-old. The 0-4-year-old had 8% higher ciprofloxacin susceptibility. Only erythromycin susceptibility varied by sex, being higher in males. Escherichia coli ciprofloxacin susceptibility in blood (57%) was higher than in urine (39%) or pus (28%), as was ceftriaxone susceptibility in blood (44%) versus urine (34%) or pus (14%). Klebsiella spp. susceptibility to ciprofloxacin and meropenem decreased by 55% and 47%, respectively, during the evaluation period. During the same period, Escherichia coli ciprofloxacin susceptibility decreased by 40%, while Staphylococcus aureus gentamicin susceptibility decreased by 37%. Resistance was high across the Access and Watch antibiotic categories, varying with time, age, sex, specimen type, and hospital unit. Effective antimicrobial stewardship targeted at the critical AMR drivers is urgently needed.

Bus Riding as Amplification Mechanism for SARS-CoV-2 Transmission, Germany, 20211.

To examine the risk associated with bus riding and identify transmission chains, we investigated a COVID-19 outbreak in Germany in 2021 that involved index case-patients among bus-riding students. We used routine surveillance data, performed laboratory analyses, interviewed case-patients, and conducted a cohort study. We identified 191 case-patients, 65 (34%) of whom were elementary schoolchildren. A phylogenetically unique strain and epidemiologic analyses provided a link between air travelers and cases among bus company staff, schoolchildren, other bus passengers, and their respective household members. The attack rate among bus-riding children at 1 school was ≈4 times higher than among children not taking a bus to that school. The outbreak exemplifies how an airborne agent may be transmitted effectively through (multiple) short (<20 minutes) public transport journeys and may rapidly affect many persons.

Epidemiology of Escherichia coli bloodstream infection antimicrobial resistance trends across South West England during the first 2 years of the coronavirus disease 2019 pandemic response

ObjectivesBetween 2016 and 2019, the proportion of Escherichia coli bloodstream infection (BSI) with resistance to at least one antibiotic increased nationally. Public health interventions implemented in response to the COVID-19 pandemic changed population contact patterns and healthcare systems, with consequent effects on epidemiological trends of numerous pathogens. We investigated the impact of COVID-19 restrictions on epidemiological trends of E. coli BSI antimicrobial resistance (AMR) across South West England. MethodsWe undertook a retrospective ecological analysis utilizing routine surveillance data of E. coli BSI cases reported to the UK Health Security Agency between 2016 and 2021. We analysed AMR trends for antimicrobial agents including amoxicillin–clavulanate, ciprofloxacin, piperacillin–tazobactam, gentamicin, third-generation cephalosporins and carbapenems before and after the implementation of COVID-19 restrictions (23 March 2020) using Bayesian segmented regression. ResultsWe identified 19 055 cases. A total of 50.2% were male. Median age was 76 (interquartile range, 65–85 years). Piperacillin–tazobactam (–2.90% [95% highest density interval {HDI} –4.51%, –0.48%]) and ciprofloxacin (–2.40% [95% HDI –4.35%, 0.48%]) resistance demonstrated immediate step changes at the implementation of COVID-19 restrictions. Gentamicin (odds ratio [OR] 0.92 [95% HDI 0.76, 1.12]) and third-generation cephalosporins (OR 0.95 [95% HDI 0.80, 1.14]) exhibited decreasing annual resistance trends after the implementation of COVID-19 restrictions, with moderate evidence for a lower OR after restrictions as compared to the period before (gentamicin Bayes Factor = 5.10, third-generation cephalosporins Bayes Factor = 6.67). DiscussionCOVID-19 restrictions led to abrupt and longer term changes to E.coli BSI AMR. The immediate effects suggest altered transmission, whereas changes to resistant E. coli reservoirs may explain trend effects.

Application of the screening method for estimating COVID-19 vaccine effectiveness using routine surveillance data: Germany's experience during the COVID-19 pandemic, July 2021 to March 2023.

The screening method represents a simple, quick, and practical tool for estimating vaccine effectiveness (VE) using routine disease surveillance and vaccine coverage data, even if these data cannot be linked. In Germany, where notification data, laboratory testing data, and vaccine coverage data cannot be linked due to strict data protection requirements, the screening method was used to assess COVID-19 VE continuously between July 2021 and March 2023. During this period, when Delta and Omicron variants circulated, VE estimates were produced in real-time for different age groups and clinical outcomes. Here we describe the country's overall positive experience using the screening method, including its strengths and limitations, and provide practical guidance regarding a few issues, such as case definition stringency, testing behaviour, and data stratification, that require careful consideration during data analysis and the interpretation of the results.

The prevalence of gestational syphilis in Malawi between 2014 and 2022: spatiotemporal modeling of population-level factors.

Mother-to-child transmission of syphilis remains high especially in the WHO AFRO region with a prevalence of 1.62%, resulting in a congenital syphilis rate of 1,119 per 100,000 live births. Elimination efforts can be supported by an understanding of the spatial and temporal changes in disease over time, which can identify priority areas for targeted interventions aimed at reducing transmission. We collated routine surveillance data from health facilities and covariate data from demographic and health surveys conducted in Malawi between 2014 and 2022. We fitted a Bayesian hierarchical mixed model with spatial and temporally structured random effects to model the district-level monthly counts of maternal syphilis notifications as a function of individual- and district-level predictors. We then generated district-level spatiotemporally explicit risk profiles to estimate the effect of individual- and district-level covariates on maternal syphilis notifications and to identify hotspot areas. Overall, the national prevalence of maternal syphilis increased from 0.28% (95% CI: 0.27-0.29%) in 2014 to peaking in 2021 at 1.92% (95% CI: 1.89-1.96%). Between 2020 and 2022, there was a decline in prevalence, with the most significant decline seen in Zomba District (1.40, 95% CI: 1.12-1.66%). In regression models, a one percentage point increase in district-level antenatal HIV prevalence was associated with increased maternal syphilis (prevalence ratio [PR]: 1.15, 95% credible interval [CrI]: 1.10-1.21). There was also an increased prevalence of maternal syphilis associated with an increased district-level mean number of sex partners (PR: 1.05, 95% CrI: 0.80-1.37). The number of districts with a high prevalence of maternal syphilis also increased between 2014 and 2022, especially in the southern region, where most had a high probability (approaching 100%) of having high maternal syphilis (defined as relative risk >1 compared to the standard population of women aged 15-49 years) in 2022. Maternal syphilis prevalence in Malawi shows an increasing upward trend, with an estimated six times relative increase between 2014 and 2022 (0.28% to 1.73%) and strong associations with higher district-level HIV prevalence. Controlling syphilis depends on reaching vulnerable populations at the sub-national level, which may be disproportionately affected. Our findings support the move to integrate the elimination of mother-to-child transmission (EMTCT) of syphilis programs with existing prevention of mother-to-child transmission (PMTCT) of HIV programs.

Early Prediction of Autistic Spectrum Disorder Using Developmental Surveillance Data

With the continuous increase in the prevalence of autistic spectrum disorder (ASD), effective early screening is crucial for initiating timely interventions and improving outcomes. To develop predictive models for ASD using routinely collected developmental surveillance data and to assess their performance in predicting ASD at different ages and in different clinical scenarios. This retrospective cohort study used nationwide data of developmental assessments conducted between January 1, 2014, and January 17, 2023, with minimal follow-up of 4 years and outcome collection in March 2023. Data were from a national program of approximately 1000 maternal child health clinics that perform routine developmental surveillance of children from birth to 6 years of age, serving 70% of children in Israel. The study included all children who were assessed at the maternal child health clinics (N = 1 187 397). Children were excluded if they were born at a gestational age of 33 weeks or earlier, had no record of gestational age, or were followed up for less than 4 years without an ASD outcome. The data set was partitioned at random into a development set (80% of the children) and a holdout evaluation set (20% of the children), both with the same prevalence of ASD outcome. For each child, demographic and birth-related covariates were extracted, as were per-visit growth measurements, quantified developmental milestone assessments, and referral summary covariates. Only information that was available before the prediction age was used for training and evaluating the models. The main outcome was eligibility for a governmental disabled child allowance due to ASD, according to administrative data of the National Insurance Institute of Israel. The performance of the models that predict the outcome was evaluated and compared with previous work on the Modified Checklist for Autism in Toddlers (M-CHAT). The study included 1 187 397 children (610 588 [51.4%] male). The performance of the ASD prediction models improved with prediction age, with fair accuracy already at 12 months of age. A model that combined longitudinal measures of developmental milestone assessments with a minimal set of demographic variables, which was applied at 18 to 24 months of age, achieved an area under the receiver operating characteristic curve of 0.83, with a sensitivity of 45.1% at a specificity of 95.0%. A model using single-visit assessments achieved an area under the receiver operating characteristic curve of 0.81 and a sensitivity of 41.2% at a specificity of 95.0%. The best performing prediction models surpassed the pooled performance of M-CHAT (sensitivity, 40%; specificity, 95%) reported in studies with a similar design. This cohort study found that ASD can be predicted from routine developmental surveillance data at an accuracy surpassing M-CHAT screening. This tool may be seamlessly integrated in the clinical workflow to improve early identification of children who may benefit from timely interventions.