Comparison of statistical methods for the early detection of disease outbreaks in small population settings.

Objectives: This study examines the performance of 6 aberration detection algorithms for the early detection of disease outbreaks in small population settings using syndrome-based early warning surveillance data collected by the Pacific Syndromic Surveillance System (PSSS). Although previous studies have proposed statistical methods for detecting aberrations in larger datasets, there is limited knowledge about how these perform in the presence of small numbers of background cases. Methods: To address this gap a simulation model was developed to test and compare the performance of the 6 algorithms in detecting outbreaks of different magnitudes, durations, and case distributions. Results: The study found that while the Early Aberration Reporting System-C1 algorithm developed by Hutwagner et al. outperformed others, no single approach provided reliable monitoring across all outbreak types. Furthermore, aberration detection approaches could only detect very large and acute outbreaks with any reliability. Conclusion: The findings of this study suggest that algorithm-based approaches to outbreak signal detection perform poorly when applied to settings with small numbers of background cases and should not be relied upon in these contexts. This highlights the need for alternative approaches for accurate and timely outbreak detection in small population settings, particularly those that are resource-constrained.

Sex differences in sepsis hospitalisations and outcomes in older women and men: A prospective cohort study.

PURPOSE: To examine the association of sex with hospitalisation due to sepsis and related outcomes. METHODS: Prospective cohort study of 264,678 adults, average age 62.7 years at recruitment (2006-2009) in Australia. Participants were followed for sepsis hospitalisation identified using the International Classification of Diseases coding. Outcomes included sex differences in the risk of an incident sepsis hospitalisation, mortality, length of ICU and hospital stay and readmissions during the following year. RESULTS: Over 2,070,343 years of follow-up there were 12,912 sepsis hospitalisations, 59.6% in men. Age-standardised risk of hospitalisation was higher in men versus women (10.37 vs 6.77 per 1,000 person years; age-adjusted HR 1.58; 95% CI 1.53-1.59) and did not attenuate after adjusting for sociodemographics, health behaviours and co-morbidities. Relative risks were similar for sepsis-related ICU admissions (adjusted HR 1.72; 95% CI 1.57-1.88). Death at one year was more common in men than women (39.3% vs 33.7% p<0.001). After adjusting for age, men had a longer hospital (12.0 vs 11.2 days; p<0.001) and ICU (6.5 vs 5.8 days; p<0.001) stays and were more likely to be readmitted to hospital for sepsis (22.3 vs 19.4%; p<0.001) or any reason (73.0% vs 70.7%; p<0.001) at one year. CONCLUSION: In older adults, compared to women, men are at an increased risk of sepsis hospitalisation, sepsis-related ICU admission, death and readmission to hospital within one year after a sepsis hospitalisation. Understanding these sex differences and their mechanisms may offer opportunities for better prevention and management and improved patient outcomes.

Understanding COVID-19 dynamics and the effects of interventions in the Philippines: A mathematical modelling study.

BACKGROUND: COVID-19 initially caused less severe outbreaks in many low- and middle-income countries (LMIC) compared with many high-income countries, possibly because of differing demographics, socioeconomics, surveillance, and policy responses. Here, we investigate the role of multiple factors on COVID-19 dynamics in the Philippines, a LMIC that has had a relatively severe COVID-19 outbreak. METHODS: We applied an age-structured compartmental model that incorporated time-varying mobility, testing, and personal protective behaviors (through a "Minimum Health Standards" policy, MHS) to represent the first wave of the Philippines COVID-19 epidemic nationally and for three highly affected regions (Calabarzon, Central Visayas, and the National Capital Region). We estimated effects of control measures, key epidemiological parameters, and interventions. FINDINGS: Population age structure, contact rates, mobility, testing, and MHS were sufficient to explain the Philippines epidemic based on the good fit between modelled and reported cases, hospitalisations, and deaths. The model indicated that MHS reduced the probability of transmission per contact by 13-27%. The February 2021 case detection rate was estimated at ~8%, population recovered at ~9%, and scenario projections indicated high sensitivity to MHS adherence. INTERPRETATION: COVID-19 dynamics in the Philippines are driven by age, contact structure, mobility, and MHS adherence. Continued compliance with low-cost MHS should help the Philippines control the epidemic until vaccines are widely distributed, but disease resurgence may be occurring due to a combination of low population immunity and detection rates and new variants of concern.

Estimating pertussis incidence in general practice using a large Australian primary care database.

BACKGROUND: While pertussis is notifiable in most countries, notifications typically underestimate the true pertussis burden. We explored the incidence of pertussis in general practice in Australia. METHODS: Using MedicineInsight, a large longitudinal electronic medical record database of general practice (primary care) encounters which includes >1.5 million patients, we first defined a cohort of active patients and then used free-text search algorithms to identify patients with pertussis-related encounters. We defined and identified pertussis-related encounters in four patient categories: pertussis-associated (category 1), potential pertussis (category 2), epidemiologically-linked pertussis (category 3), and symptoms consistent with pertussis (category 4). Incident pertussis-related encounter rates per 100,000 active patients were calculated from Jan 2008 to Aug 2015. RESULTS: Estimated mean annual pertussis incidence increased as definitions were expanded, from 94.3 (category 1 patients only) to 148.8 (categories 1+2+3 patients combined) per 100,000 active patients per year. Monthly time-series corresponding to the first three categories were highly correlated (Pearson's r > 90% for each pair), but each was poorly correlated with category 4. For categories 1+2+3, the highest incidence was among 0-4 and 5-9 year olds. Incidence was 30% higher in females than males (i.e. 184.5 vs 139.8 per 100,00 active patients for categories 1-3 patients combined). Pertussis-associated incidence (category 1) was similar to national pertussis notification rates. Categories 2 and 3 added 25% and 33%, respectively, on average relative to category 1 incidence. The estimated incidence from categories 1+2+3 together were on average 64% higher than national pertussis notification rates. CONCLUSION: We provide comprehensive estimates of pertussis-related incidence in general practice (primary care), well in excess of notified pertussis incidence in Australia. This highlights the utility of MedicineInsight data in providing a greater understanding of the burden of medically-attended pertussis infections.

Incidence and outcomes of sepsis in Aboriginal and Torres Strait Islander and non-Indigenous residents of New South Wales: population-based cohort study.

Objective: To estimate the incidence and outcomes of sepsis hospitalisations in Aboriginal and Torres Strait Islander and non-Indigenous residents of New South Wales. Design and participants: Prospective cohort study of residents aged 45 years and older, recruited between 2006 and 2009, and followed for hospitalisation for sepsis. Main outcome measures: Incidence and hazard ratio (HR) of sepsis hospitalisation and intensive care unit (ICU) admission identified using International Classification of Diseases (10th revision) coding on discharge data. Length of stay, readmission and mortality in those admitted for sepsis. Results: Of 264 678 participants, 1928 (0.7%) identified as Aboriginal and/or Torres Strait Islander. Sepsis hospitalisation was higher in Aboriginal and Torres Strait Islander participants (8.67 v 6.12 per 1000 person-years; age- and sex-adjusted HR, 2.35; 95% CI, 1.98-2.80) but was attenuated after adjusting for sociodemographic factors, health behaviour and comorbidities (adjusted HR, 1.56; 95% CI, 1.31-1.86). Among those hospitalised for sepsis, after adjusting for age and sex, there were no differences between the proportions of Aboriginal and Torres Strait Islander and non-Indigenous participants admitted to an ICU (18.0% v 16.1%; P = 0.42) or deceased at 1 year (36.1% v 36.8%; P = 0.92). Aboriginal and Torres Strait Islander participants had shorter lengths of hospital stay (9.98 v 11.72 days; P < 0.001) and ICU stay (4.38 v 6.35 days; P < 0.001) than non-Indigenous participants. Overall, more than 70% of participants were readmitted to hospital within 1 year. Conclusion: We found that the rate of sepsis hospitalisation in NSW was higher for Aboriginal and Torres Strait Islander adults. Culturally appropriate, community-led strategies targeting chronic disease prevention and the social determinants of health may reduce this gap. Preventing readmission following sepsis is a priority for all Australians.

High healthcare resource utilisation due to pertussis in Australian adults aged 65 years and over.

BACKGROUND: In the context of co-morbid illness and increasing age, data on excess morbidity from pertussis in older adults is crucial for immunisation policy but has been largely limited to case-series. METHODS: We designed a matched case-control study nested within a population-based cohort of 267,153 adults aged ≥45 years in New South Wales, Australia (The 45 and Up Study cohort). Excess hospital bed days, emergency department (ED) admissions, general practitioner (GP) visits, and prescriptions were estimated using negative binomial regression models. An additional self-controlled analysis was also conducted to validate the main models, and to evaluate results for those with either asthma or a body mass index (BMI)≥30 compared to those without these risk factors. RESULTS: Based on 524 pairs of PCR-confirmed pertussis cases and matched controls, we estimated an excess healthcare utilisation per case of 2.5 prescriptions (95% CI: 0.2-4.7), of which 1.1 (95% CI: 0.5-2.2) were antibiotics, 2.3 GP visits (95% CI: 2.0-2.6), and 0.1 ED admissions (95% CI: 0.1-0.2). Compared to those 45-64 years, cases ≥65 years had a significantly greater excess for all prescriptions (1.1 vs 4.7/case), antibiotic prescriptions (0.1 vs 2.2/case), and ED admissions (0.1 vs 0.2/case), but no significant excess of respiratory-related hospital bed days. An additional self-controlled analysis confirmed that cases with either asthma or BMI≥30 had higher overall healthcare utilisation but this was not associated with pertussis infection. CONCLUSION: We found a substantial excess outpatient healthcare burden among adults aged 65 years and over with PCR-confirmed pertussis, supporting further evaluation of preventive measures.

Rapid mapping of the spatial and temporal intensity of influenza.

Surveillance of influenza epidemics is a priority for risk assessment and pandemic preparedness, yet representation of their spatiotemporal intensity remains limited. Using the epidemic of influenza type A in 2016 in Australia, we demonstrated a simple but statistically sound adaptive method of mapping epidemic evolution over space and time. Weekly counts of persons with laboratory confirmed influenza type A infections in Australia in 2016 were analysed by official national statistical region. Weekly standardised epidemic intensity was represented by a standard score (z-score) calculated using the standard deviation of below-median counts in the previous 52 weeks. A geographic information system (GIS) was used to present the epidemic progression. There were 79,628 notifications of influenza A infections included. Of these, 79,218 (99.5%) were allocated to a geographical area. The GIS maps indicated areas of elevated epidemic intensity across Australia by week and area that were consistent with the observed start, peak and decline of the epidemic when compared with counts aggregated at the state and territory level. This simple, adaptable approach could improve local level epidemic intelligence in a variety of settings and for other diseases. It may also facilitate increased understanding of geographic epidemic dynamics.

Spatial analysis of the distribution of reported dengue incidence in the National Capital Region, Philippines

BACKGROUND AND OBJECTIVE: With an aim of developing an effective disease monitoring and surveillance of dengue fever, this study intends to analyze the spatial distribution of dengue incidences in the National Capital Region (NCR), across four years of reported dengue cases.MATERIALS AND METHODS: Data used was provided by the Department of Health (DOH) consisting of all reported dengue cases in NCR from 2010-2013. For mapping and visualization, a shapefile of NCR was made readily available by www.philgis.org. Both Moran's I and Kulldorff's spatial scan statistics (SaTScan) were used to identify clusters across the same time period.RESULTS AND CONCLUSION: The analyses identified significant clustering of dengue incidence and revealed that the northern cities of NCR, such as Caloocan, Malabon, Navotas and Valenzuela, exhibited high spatial autocorrelation using local Moran's I and Kulldorff's SaTScan. A temporal analysis of the results also suggested movement in increased dengue incidence through time, from the northwest cities to the northeast cities. Presence of spatial autocorrelation in dengue incidence suggests possible enhancements of early detection schemes for dengue surveillance. Moreover, the results of these analyses will be of interest to both policymakers and health experts in providing a basis for which they can properly allocate resources for the prevention and treatment of dengue fever.