Assessing the impact of Australia's mass vaccination campaigns over the Delta and Omicron outbreaks

BACKGROUND

The Australian Government implemented a national vaccination campaign against COVID-19 beginning February 22, 2021. The roll-out was criticised for being delayed relative to many high-income countries, but high levels of vaccination coverage were belatedly achieved. The large-scale Omicron outbreak in January 2022 resulted in a massive number of cases and deaths, although mortality would have been far higher if not for vigorous efforts to rapidly vaccinate the entire population. The impact of the vaccination coverage was assessed over this extended period.

METHODS

We considered NSW, as the Australian jurisdiction with the highest quality data for our purposes and which still reflected the national experience. Weekly death rates were derived among individuals aged 50+ with respect to vaccine status between August 8, 2021 and July 9, 2022. We evaluated deaths averted by the vaccination campaign by modelling alternative counterfactual scenarios based on a simple data-driven modelling methodology presented by Jia et al. (2023).

FINDINGS

Unvaccinated individuals had a 7.7-fold greater mortality rate than those who were fully vaccinated among people aged 50+, which rose to 11.2-fold in those who had received a booster dose. If NSW had fully vaccinated its ~2.9 million 50+ residents earlier (by July 28, 2021), only 440 of the total 3,495 observed 50+ deaths would have been averted. Up to July 9, 2022, the booster campaign prevented 1,860 deaths. In the absence of a vaccination campaign, ~21,250 COVID-19 50+ deaths (conservative estimate) could have been expected in NSW i.e., some 6 times the actual total. We also find the methodology of Jia et al. (2023) can sometimes significantly underestimate that actual number.

INTERPRETATION

The Australian vaccination campaign was successful in reducing mortality over 2022, relative to alternative hypothetical vaccination scenarios. The success was attributable to the Australian public's high levels of engagement with vaccination in the face of new SARS-COV-2 variants, and because high levels of vaccination coverage (full and booster) were achieved in the period shortly before the major Omicron outbreak of 2022.

The prevalence of tuberculosis infection among foreign-born Canadians: a modelling study

BACKGROUND

The prevalence of tuberculosis infection is critical to the design of tuberculosis prevention strategies, yet is unknown in Canada. We estimated the prevalence of tuberculosis infection among Canadian residents born abroad.

METHODS

We estimated the prevalence of tuberculosis infection by age and year of migration to Canada for people from each of 168 countries by constructing country-specific and calendar year-specific trends for annual risk of infection using a previously developed model. We combined country-specific prevalence estimates with Canadian Census data from 2001, 2006, 2011, 2016 and 2021 to estimate the overall prevalence of tuberculosis infection among foreign-born Canadian residents.

RESULTS

The estimated overall prevalence of tuberculosis infection among foreign-born people in Canada was 25% (95% uncertainty interval [UI] 20%-35%) for census year 2001, 24% (95% UI 20%-33%) for 2006, 23% (95% UI 19%-30%) for 2011, 22% (95% UI 19%-28%) for 2016 and 22% (95% UI 19%-27%) for 2021. The prevalence increased with age at migration and incidence of tuberculosis in the country of origin. In 2021, the estimated prevalence of infection among foreign-born residents was lowest in Quebec (19%, 95% UI 16%-24%) and highest in Alberta (24%, 95% UI 21%-28%) and British Columbia (24%, 95% UI 20%-30%). Among all foreign-born Canadian residents with tuberculosis infection in 2021, we estimated that only 1 in 488 (95% UI 185-1039) had become infected within the 2 preceding years.

INTERPRETATION

About 1 in 4 foreign-born Canadian residents has tuberculosis infection, but very few were infected within the 2 preceding years (the highest risk period for progression to tuberculosis disease). These data may inform future tuberculosis infection screening policies.

Literature Highlights

Literature Highlights is a digest of notable papers recently published in the leading respiratory journals, allowing our readers to stay up-to-date with research advances. Coverage in this issue includes Vitamin D supplementation to prevent TB infection; network models of TB dynamics through enhanced data collection linked to active case-finding; hydrocortisone use for severe community-acquired pneumonia; and low-cost air quality sensors and individual exposure levels.

Finding and treating both tuberculosis disease and latent infection during population-wide active case finding for tuberculosis elimination

In recognition of the high rates of undetected tuberculosis in the community, the World Health Organization (WHO) encourages targeted active case finding (ACF) among "high-risk" populations. While this strategy has led to increased case detection in these populations, the epidemic impact of these interventions has not been demonstrated. Historical data suggest that population-wide (untargeted) ACF can interrupt transmission in high-incidence settings, but implementation remains lacking, despite recent advances in screening tools. The reservoir of latent infection-affecting up to a quarter of the global population -complicates elimination efforts by acting as a pool from which future tuberculosis cases may emerge, even after all active cases have been treated. A holistic case finding strategy that addresses both active disease and latent infection is likely to be the optimal approach for rapidly achieving sustainable progress toward TB elimination in a durable way, but safety and cost effectiveness have not been demonstrated. Sensitive, symptom-agnostic community screening, combined with effective tuberculosis treatment and prevention, should eliminate all infectious cases in the community, whilst identifying and treating people with latent infection will also eliminate tomorrow's tuberculosis cases. If real strides toward global tuberculosis elimination are to be made, bold strategies are required using the best available tools and a long horizon for cost-benefit assessment.

Literature Highlights

Literature Highlights is a digest of notable papers recently published in the leading respiratory journals, allowing our readers to stay up-to-date with research advances. Coverage in this issue includes time to smear and culture conversion during TB treatment; probability of diagnosing ventilator-associated pneumonia in intensive care and use of antimicrobials; optimising computer-aided chest X-ray to diagnose intra-thoracic TB in children; and clinical standards for asthma in low- and middle-income countries.

Replicating superspreader dynamics with compartmental models

Infectious disease outbreaks often exhibit superspreader dynamics, where most infected people generate no, or few secondary cases, and only a small fraction of individuals are responsible for a large proportion of transmission. Although capturing this heterogeneity is critical for estimating outbreak risk and the effectiveness of group-specific interventions, it is typically neglected in compartmental models of infectious disease transmission-which constitute the most common transmission dynamic modeling framework. In this study we propose different classes of compartmental epidemic models that incorporate transmission heterogeneity, fit them to a number of real outbreak datasets, and benchmark their performance against the canonical superspreader model (i.e., the negative binomial branching process model). We find that properly constructed compartmental models can capably reproduce observed superspreader dynamics and we provide the pathogen-specific parameter settings required to do so. As a consequence, we also show that compartmental models parameterized according to a binary clinical classification have limited support.

Mental health and wellbeing of health and aged care workers in Australia, May 2021 - June 2022: a longitudinal cohort study

OBJECTIVES

To assess the mental health and wellbeing of health and aged care workers in Australia during the second and third years of the coronavirus disease 2019 (COVID-19) pandemic, overall and by occupation group.

DESIGN, SETTING, PARTICIPANTS

Longitudinal cohort study of health and aged care workers (ambulance, hospitals, primary care, residential aged care) in Victoria: May-July 2021 (survey 1), October-December 2021 (survey 2), and May-June 2022 (survey 3).

MAIN OUTCOME MEASURES

Proportions of respondents (adjusted for age, gender, socio-economic status) reporting moderate to severe symptoms of depression (Patient Health Questionnaire-9, PHQ-9), anxiety (Generalized Anxiety Disorder scale, GAD-7), or post-traumatic stress (Impact of Event Scale-6, IES-6), burnout (abbreviated Maslach Burnout Inventory, aMBI), or high optimism (10-point visual analogue scale); mean scores (adjusted for age, gender, socio-economic status) for wellbeing (Personal Wellbeing Index-Adult, PWI-A) and resilience (Connor Davidson Resilience Scale 2, CD-RISC-2).

RESULTS

A total of 1667 people responded to at least one survey (survey 1, 989; survey 2, 1153; survey 3, 993; response rate, 3.3%). Overall, 1211 survey responses were from women (72.6%); most respondents were hospital workers (1289, 77.3%) or ambulance staff (315, 18.9%). The adjusted proportions of respondents who reported moderate to severe symptoms of depression (survey 1, 16.4%; survey 2, 22.6%; survey 3, 19.2%), anxiety (survey 1, 8.8%; survey 2, 16.0%; survey 3, 11.0%), or post-traumatic stress (survey 1, 14.6%; survey 2, 35.1%; survey 3, 14.9%) were each largest for survey 2. The adjusted proportions of participants who reported moderate to severe symptoms of burnout were higher in surveys 2 and 3 than in survey 1, and the proportions who reported high optimism were smaller in surveys 2 and 3 than in survey 1. Adjusted mean scores for wellbeing and resilience were similar at surveys 2 and 3 and lower than at survey 1. The magnitude but not the patterns of change differed by occupation group.

CONCLUSION

Burnout was more frequently reported and mean wellbeing and resilience scores were lower in mid-2022 than in mid-2021 for Victorian health and aged care workers who participated in our study. Evidence-based mental health and wellbeing programs for workers in health care organisations are needed.

TRIAL REGISTRATION

Australian New Zealand Clinical Trials Registry: ACTRN12621000533897 (observational study; retrospective).

Literature Highlights

Literature Highlights is a digest of notable papers recently published in the leading respiratory journals. Coverage includes a 6-month, all-oral regimen for rifampicin-resistant TB; phase 3 trials of two shorter regimen for drug-resistant TB; heterogeneity in M. tuberculosis transmission through whole-genome sequencing; vaping and pulmonary inflammation; impact of COVID-19 during pregnancy on mother and newborn; migrants and TB.

Tuberculosis notifications in regional Victoria, Australia: Implications for public health care in a low incidence setting

BACKGROUND

Regionality is often a significant factor in tuberculosis (TB) management and outcomes worldwide. A wide range of context-specific factors may influence these differences and change over time. We compared TB treatment in regional and metropolitan areas, considering demographic and temporal trends affecting TB diagnosis and outcomes.

METHODS

Retrospective analyses of data for patients notified with TB in Victoria, Australia, were conducted. The study outcomes were treatment delays and treatment outcomes. Multivariable Cox proportional hazard model analyses were performed to investigate the effect of regionality in the management of TB. Six hundred and eleven (7%) TB patients were notified in regional and 8,163 (93%) in metropolitan areas between 1995 and 2019. Of the 611 cases in the regional cohort, 401 (66%) were overseas-born. Fifty-one percent of the overseas-born patients in regional Victoria developed TB disease within five years of arrival in Australia. Four cases of multidrug-resistant tuberculosis were reported in regional areas, compared to 97 cases in metropolitan areas. A total of 3,238 patients notified from 2012 to 2019 were included in the survival analysis. The time follow-up for patient delay started at symptom onset date, and the event was the presentation to the healthcare centre. For healthcare system delay, follow-up time began at the presentation to the healthcare centre, and the event was commenced on TB treatment. Cases with extrapulmonary TB in regional areas have a non-significantly longer healthcare system delay than patients in metropolitan (median 64 days versus 54 days, AHR = 0.8, 95% CI 0.6-1.0, P = 0.094).

CONCLUSION

Tuberculosis in regional Victoria is common among the overseas-born population, and patients with extrapulmonary TB in regional areas experienced a non-significant minor delay in treatment commencement with no apparent detriment to treatment outcomes. Improving access to LTBI management in regional areas may reduce the burden of TB.

Detecting Mycobacterium tuberculosis Infection in Children Migrating to Australia

In 2015, Australia updated premigration screening for tuberculosis (TB) disease in children 2-10 years of age to include testing for infection with Mycobacterium tuberculosis and enable detection of latent TB infection (LTBI). We analyzed TB screening results in children <15 years of age during November 2015-June 2017. We found 45,060 child applicants were tested with interferon-gamma release assay (IGRA) (57.7% of tests) or tuberculin skin test (TST) (42.3% of tests). A total of 21 cases of TB were diagnosed: 4 without IGRA or TST, 10 with positive IGRA or TST, and 7 with negative results. LTBI was detected in 3.3% (1,473/44,709) of children, for 30 applicants screened per LTBI case detected. LTBI-associated factors included increasing age, TB contact, origin from a higher TB prevalence region, and testing by TST. Detection of TB and LTBI benefit children, but the updated screening program's effect on TB in Australia is likely to be limited.

Mental Health Outcomes in Australian Healthcare and Aged-Care Workers during the Second Year of the COVID-19 Pandemic

Objective: the COVID-19 pandemic has incurred psychological risks for healthcare workers (HCWs). We established a Victorian HCW cohort (the Coronavirus in Victorian Healthcare and Aged-Care Workers (COVIC-HA) cohort study) to examine COVID-19 impacts on HCWs and assess organisational responses over time. Methods: mixed-methods cohort study, with baseline data collected via an online survey (7 May–18 July 2021) across four healthcare settings: ambulance, hospitals, primary care, and residential aged-care. Outcomes included self-reported symptoms of depression, anxiety, post-traumatic stress (PTS), wellbeing, burnout, and resilience, measured using validated tools. Work and home-related COVID-19 impacts and perceptions of workplace responses were also captured. Results: among 984 HCWs, symptoms of clinically significant depression, anxiety, and PTS were reported by 22.5%, 14.0%, and 20.4%, respectively, highest among paramedics and nurses. Emotional exhaustion reflecting moderate–severe burnout was reported by 65.1%. Concerns about contracting COVID-19 at work and transmitting COVID-19 were common, but 91.2% felt well-informed on workplace changes and 78.3% reported that support services were available. Conclusions: Australian HCWs employed during 2021 experienced adverse mental health outcomes, with prevalence differences observed according to occupation. Longitudinal evidence is needed to inform workplace strategies that support the physical and mental wellbeing of HCWs at organisational and state policy levels.

Population-wide active case finding and prevention for tuberculosis and leprosy elimination in Kiribati: the PEARL study protocol

INTRODUCTION

Population-wide interventions offer a pathway to tuberculosis (TB) and leprosy elimination, but 'real-world' implementation in a high-burden setting using a combined approach has not been demonstrated. This implementation study aims to demonstrate the feasibility and evaluate the effect of population-wide screening, treatment and prevention on TB and leprosy incidence rates, as well as TB transmission.

METHODS AND ANALYSIS

A non-randomised 'screen-and-treat' intervention conducted in the Pacific atoll of South Tarawa, Kiribati. Households are enumerated and all residents ≥3 years, as well as children <3 years with recent household exposure to TB or leprosy, invited for screening. Participants are screened using tuberculin skin testing, signs and symptoms of TB or leprosy, digital chest X-ray with computer-aided detection and sputum testing (Xpert MTB/RIF Ultra). Those diagnosed with disease are referred to the National TB and Leprosy Programme for management. Participants with TB infection are offered TB preventive treatment and those without TB disease or infection, or leprosy, are offered leprosy prophylaxis. The primary study outcome is the difference in the annual TB case notification rate before and after the intervention; a similar outcome is included for leprosy. The effect on TB transmission will be measured by comparing the estimated annual risk of TB infection in primary school children before and after the intervention, as a co-primary outcome used for power calculations. Comparison of TB and leprosy case notification rates in South Tarawa (the intervention group) and the rest of Kiribati (the control group) before, during and after the intervention is a secondary outcome.

ETHICS AND DISSEMINATION

Approval was obtained from the University of Sydney Human Research Ethics Committee (project no. 2021/127) and the Kiribati Ministry of Health and Medical Services (MHMS). Findings will be shared with the MHMS and local communities, published in peer-reviewed journals and presented at international conferences.

Estimating the long-term effects of mass screening for latent and active tuberculosis in the Marshall Islands

BACKGROUND

Ambitious population-based screening programmes for latent and active tuberculosis (TB) were implemented in the Republic of the Marshall Islands in 2017 and 2018.

METHODS

We used a transmission dynamic model of TB informed by local data to capture the Marshall Islands epidemic's historical dynamics. We then used the model to project the future epidemic trajectory following the active screening interventions, as well as considering a counterfactual scenario with no intervention. We also simulated future scenarios including periodic interventions similar to those previously implemented, to assess their ability to reach the End TB Strategy targets and TB pre-elimination in the Marshall Islands.

RESULTS

The screening activities conducted in 2017 and 2018 were estimated to have reduced TB incidence and mortality by around one-third in 2020, and are predicted to achieve the End TB Strategy milestone of 50% incidence reduction by 2025 compared with 2015. Screening interventions had a considerably greater impact when latent TB screening and treatment were included, compared with active case finding alone. Such combined programmes implemented at the national level could achieve TB pre-elimination around 2040 if repeated every 2 years.

CONCLUSIONS

Our model suggests that it would be possible to achieve TB pre-elimination by 2040 in the Marshall Islands through frequent repetition of the same interventions as those already implemented in the country. It also highlights the importance of including latent infection testing in active screening activities.

Estimating tuberculosis drug resistance amplification rates in high-burden settings

Background

Antimicrobial resistance develops following the accrual of mutations in the bacterial genome, and may variably impact organism fitness and hence, transmission risk. Classical representation of tuberculosis (TB) dynamics using a single or two strain (DS/MDR-TB) model typically does not capture elements of this important aspect of TB epidemiology. To understand and estimate the likelihood of resistance spreading in high drug-resistant TB incidence settings, we used epidemiological data to develop a mathematical model of Mycobacterium tuberculosis (Mtb) transmission.

Methods

A four-strain (drug-susceptible (DS), isoniazid mono-resistant (INH-R), rifampicin mono-resistant (RIF-R) and multidrug-resistant (MDR)) compartmental deterministic Mtb transmission model was developed to explore the progression from DS- to MDR-TB in The Philippines and Viet Nam. The models were calibrated using data from national tuberculosis prevalence (NTP) surveys and drug resistance surveys (DRS). An adaptive Metropolis algorithm was used to estimate the risks of drug resistance amplification among unsuccessfully treated individuals.

Results

The estimated proportion of INH-R amplification among failing treatments was 0.84 (95% CI 0.79–0.89) for The Philippines and 0.77 (95% CI 0.71–0.84) for Viet Nam. The proportion of RIF-R amplification among failing treatments was 0.05 (95% CI 0.04–0.07) for The Philippines and 0.011 (95% CI 0.010–0.012) for Viet Nam.

Conclusion

The risk of resistance amplification due to treatment failure for INH was dramatically higher than RIF. We observed RIF-R strains were more likely to be transmitted than acquired through amplification, while both mechanisms of acquisition were important contributors in the case of INH-R. These findings highlight the complexity of drug resistance dynamics in high-incidence settings, and emphasize the importance of prioritizing testing algorithms which allow for early detection of INH-R.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07067-1.

Modeling the Cost-Effectiveness of Latent Tuberculosis Screening and Treatment Strategies in Recent Migrants to a Low-Incidence Setting

Many tuberculosis (TB) cases in low-incidence settings are attributed to reactivation of latent TB infection (LTBI) acquired overseas. We assessed the cost-effectiveness of community-based LTBI screening and treatment strategies in recent migrants to a low-incidence setting (Australia). A decision-analytical Markov model was developed that cycled 1 migrant cohort (≥11-year-olds) annually over a lifetime from 2020. Postmigration/onshore and offshore (screening during visa application) strategies were compared with existing policy (chest x-ray during visa application). Outcomes included TB cases averted and discounted cost per quality-adjusted life-year (QALY) gained from a health-sector perspective. Most recent migrants are young adults and cost-effectiveness is limited by their relatively low LTBI prevalence, low TB mortality risks, and high emigration probability. Onshore strategies cost at least $203,188 (Australian) per QALY gained, preventing approximately 2.3%-7.0% of TB cases in the cohort. Offshore strategies (screening costs incurred by migrants) cost at least $13,907 per QALY gained, preventing 5.5%-16.9% of cases. Findings were most sensitive to the LTBI treatment quality-of-life decrement (further to severe adverse events); with a minimal decrement, all strategies caused more ill health than they prevented. Additional LTBI strategies in recent migrants could only marginally contribute to TB elimination and are unlikely to be cost-effective unless screening costs are borne by migrants and potential LTBI treatment quality-of-life decrements are ignored.

Understanding how Victoria, Australia gained control of its second COVID-19 wave

During 2020, Victoria was the Australian state hardest hit by COVID-19, but was successful in controlling its second wave through aggressive policy interventions. We calibrated a detailed compartmental model of Victoria's second wave to multiple geographically-structured epidemic time-series indicators. We achieved a good fit overall and for individual health services through a combination of time-varying processes, including case detection, population mobility, school closures, physical distancing and face covering usage. Estimates of the risk of death in those aged ≥75 and of hospitalisation were higher than international estimates, reflecting concentration of cases in high-risk settings. We estimated significant effects for each of the calibrated time-varying processes, with estimates for the individual-level effect of physical distancing of 37.4% (95%CrI 7.2-56.4%) and of face coverings of 45.9% (95%CrI 32.9-55.6%). That the multi-faceted interventions led to the dramatic reversal in the epidemic trajectory is supported by our results, with face coverings likely particularly important.

Modelling direct and herd protection effects of vaccination against the SARS-CoV-2 Delta variant in Australia

OBJECTIVES

To analyse the outcomes of COVID-19 vaccination by vaccine type, age group eligibility, vaccination strategy, and population coverage.

DESIGN

Epidemiologic modelling to assess the final size of a COVID-19 epidemic in Australia, with vaccination program (Pfizer, AstraZeneca, mixed), vaccination strategy (vulnerable first, transmitters first, untargeted), age group eligibility threshold (5 or 15 years), population coverage, and pre-vaccination effective reproduction number ( R eff v ¯ ) for the SARS-CoV-2 Delta variant as factors.

MAIN OUTCOME MEASURES

Numbers of SARS-CoV-2 infections; cumulative hospitalisations, deaths, and years of life lost.

RESULTS

Assuming R eff v ¯ = 5, the current mixed vaccination program (vaccinating people aged 60 or more with the AstraZeneca vaccine and people under 60 with the Pfizer vaccine) will not achieve herd protection unless population vaccination coverage reaches 85% by lowering the vaccination eligibility age to 5 years. At R eff v ¯ = 3, the mixed program could achieve herd protection at 60-70% population coverage and without vaccinating 5-15-year-old children. At R eff v ¯ = 7, herd protection is unlikely to be achieved with currently available vaccines, but they would still reduce the number of COVID-19-related deaths by 85%.

CONCLUSION

Vaccinating vulnerable people first is the optimal policy when population vaccination coverage is low, but vaccinating more socially active people becomes more important as the R eff v ¯ declines and vaccination coverage increases. Assuming the most plausible R eff v ¯ of 5, vaccinating more than 85% of the population, including children, would be needed to achieve herd protection. Even without herd protection, vaccines are highly effective in reducing the number of deaths.

Timing of Mycobacterium tuberculosis exposure explains variation in BCG effectiveness: a systematic review and meta-analysis

RATIONALE

The heterogeneity in efficacy observed in studies of BCG vaccination is not fully explained by currently accepted hypotheses, such as latitudinal gradient in non-tuberculous mycobacteria exposure.

METHODS

We updated previous systematic reviews of the effectiveness of BCG vaccination to 31 December 2020. We employed an identical search strategy and inclusion/exclusion criteria to these earlier reviews, but reclassified several studies, developed an alternative classification system and considered study demography, diagnostic approach and tuberculosis (TB)-related epidemiological context.

MAIN RESULTS

Of 21 included trials, those recruiting neonates and children aged under 5 were consistent in demonstrating considerable protection against TB for several years. Trials in high-burden settings with shorter follow-up also showed considerable protection, as did most trials in settings of declining burden with longer follow-up. However, the few trials performed in high-burden settings with longer follow-up showed no protection, sometimes with higher case rates in the vaccinated than the controls in the later follow-up period.

CONCLUSIONS

The most plausible explanatory hypothesis for these results is that BCG protects against TB that results from exposure shortly after vaccination. However, we found no evidence of protection when exposure occurs later from vaccination, which would be of greater importance in trials in high-burden settings with longer follow-up. In settings of declining burden, most exposure occurs shortly following vaccination and the sustained protection observed for many years thereafter represents continued protection against this early exposure. By contrast, in settings of continued intense transmission, initial protection subsequently declines with repeated exposure to Mycobacterium tuberculosis or other pathogens.

Sustaining effective COVID-19 control in Malaysia through large-scale vaccination

INTRODUCTION

As of 3rd June 2021, Malaysia is experiencing a resurgence of COVID-19 cases. In response, the federal government has implemented various non-pharmaceutical interventions (NPIs) under a series of Movement Control Orders and, more recently, a vaccination campaign to regain epidemic control. In this study, we assessed the potential for the vaccination campaign to control the epidemic in Malaysia and four high-burden regions of interest, under various public health response scenarios.

METHODS

A modified susceptible-exposed-infectious-recovered compartmental model was developed that included two sequential incubation and infectious periods, with stratification by clinical state. The model was further stratified by age and incorporated population mobility to capture NPIs and micro-distancing (behaviour changes not captured through population mobility). Emerging variants of concern (VoC) were included as an additional strain competing with the existing wild-type strain. Several scenarios that included different vaccination strategies (i.e. vaccines that reduce disease severity and/or prevent infection, vaccination coverage) and mobility restrictions were implemented.

RESULTS

The national model and the regional models all fit well to notification data but underestimated ICU occupancy and deaths in recent weeks, which may be attributable to increased severity of VoC or saturation of case detection. However, the true case detection proportion showed wide credible intervals, highlighting incomplete understanding of the true epidemic size. The scenario projections suggested that under current vaccination rates complete relaxation of all NPIs would trigger a major epidemic. The results emphasise the importance of micro-distancing, maintaining mobility restrictions during vaccination roll-out and accelerating the pace of vaccination for future control. Malaysia is particularly susceptible to a major COVID-19 resurgence resulting from its limited population immunity due to the country's historical success in maintaining control throughout much of 2020.

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.

Revisiting the Natural History of Pulmonary Tuberculosis: A Bayesian Estimation of Natural Recovery and Mortality Rates

BACKGROUND

Tuberculosis (TB) natural history remains poorly characterized, and new investigations are impossible as it would be unethical to follow up TB patients without treatment.

METHODS

We considered the reports identified in a previous systematic review of studies from the prechemotherapy era, and extracted detailed data on mortality over time. We used a Bayesian framework to estimate the rates of TB-induced mortality and self-cure. A hierarchical model was employed to allow estimates to vary by cohort. Inference was performed separately for smear-positive TB (SP-TB) and smear-negative TB (SN-TB).

RESULTS

We included 41 cohorts of SP-TB patients and 19 cohorts of pulmonary SN-TB patients in the analysis. The median estimates of the TB-specific mortality rates were 0.389 year-1 (95% credible interval [CrI], .335-.449) and 0.025 year-1 (95% CrI, .017-.035) for SP-TB and SN-TB patients, respectively. The estimates for self-recovery rates were 0.231 year-1 (95% CrI, .177-.288) and 0.130 year-1 (95% CrI, .073-.209) for SP-TB and SN-TB patients, respectively. These rates correspond to average durations of untreated TB of 1.57 years (95% CrI, 1.37-1.81) and 5.35 years (95% CrI, 3.42-8.23) for SP-TB and SN-TB, respectively, when assuming a non-TB-related mortality rate of 0.014 year-1 (ie, a 70-year life expectancy).

CONCLUSIONS

TB-specific mortality rates are around 15 times higher for SP-TB than for SN-TB patients. This difference was underestimated dramatically in previous TB modeling studies, raising concerns about the accuracy of the associated predictions. Despite being less infectious, SN-TB may be responsible for equivalent numbers of secondary infections as SP-TB due to its much longer duration.

Geospatial clustering and modelling provide policy guidance to distribute funding for active TB case finding in Ethiopia

Tuberculosis (TB) exhibits considerable spatial heterogeneity, occurring in clusters that may act as hubs of community transmission. We evaluated the impact of an intervention targeting spatial TB hotspots in a rural region of Ethiopia. To evaluate the impact of targeted active case finding (ACF), we used a spatially structured mathematical model that has previously been described. From model equilibrium, we simulated the impact of a hotspot-targeted strategy (HTS) on TB incidence ten years from intervention commencement and the associated cost-effectiveness. HTS was also compared with an untargeted strategy (UTS). We used logistic cost-coverage analysis to estimate cost-effectiveness of interventions. At a community screening coverage level of 95 % in a hotspot region, which corresponds to screening 20 % of the total population, HTS would reduce overall TB incidence by 52 % compared with baseline. For UTS to achieve an equivalent effect, it would be necessary to screen more than 80 % of the total population. Compared to the existing passive case detection strategy, the HTS at a CDR of 75 percent in hotspot regions is expected to avert 1,023 new TB cases over ten years saving USD 170 per averted case. Similarly, at the same CDR, the UTS will detect 1316 cases over the same period saving USD 3 per averted TB case. The incremental-cost effectiveness-ratio (ICER) of UTS compared with HTS is USD 582 per averted case corresponding to 293 more TB cases averted at an additional cost of USD 170,700. Where regional TB program spending was capped at current levels, maximum gains in incidence reduction were seen when the regional budget was shared between hotspots and non-hotspot regions in the ratio of 40% : 60%. Our analysis suggests that a spatially targeted strategy is efficient and cost-saving, with the potential for significant reduction in overall TB burden.

Tuberculosis in the Western Pacific Region: Estimating the burden of disease and return on investment 2020-2030 in four countries

Background

We aimed to estimate the disease burden of Tuberculosis (TB) and return on investment of TB care in selected high-burden countries of the Western Pacific Region (WPR) until 2030.

Methods

We projected the TB epidemic in Viet Nam and Lao People's Democratic Republic (PDR) 2020–2030 using a mathematical model under various scenarios: counterfactual (no TB care); baseline (TB care continues at current levels); and 12 different diagnosis and treatment interventions. We retrieved previous modeling results for China and the Philippines. We pooled the new and existing information on incidence and deaths in the four countries, covering >80% of the TB burden in WPR. We estimated the return on investment of TB care and interventions in Viet Nam and Lao PDR using a Solow model.

Findings

In the baseline scenario, TB incidence in the four countries decreased from 97•0/100,000/year (2019) to 90•1/100,000/year (2030), and TB deaths from 83,300/year (2019) to 71,100/year (2030). Active case finding (ACF) strategies (screening people not seeking care for respiratory symptoms) were the most effective single interventions. Return on investment (2020–2030) for TB care in Viet Nam and Lao PDR ranged US$4-US$49/dollar spent; additional interventions brought up to US$2•7/dollar spent.

Interpretation

In the modeled countries, TB incidence will only modestly decrease without additional interventions. Interventions that include ACF can reduce TB burden but achieving the End TB incidence and mortality targets will be difficult without new transformational tools (e.g. vaccine, new diagnostic tools, shorter treatment). However, TB care, even at its current level, can bring a multiple-fold return on investment.

Funding

World Health Organization Western Pacific Regional Office; Swiss National Science Foundation Grant 163878.

Quantifying the rates of late reactivation tuberculosis: a systematic review

The risk of tuberculosis is greatest soon after infection, but Mycobacterium tuberculosis can remain in the body latently, and individuals can develop disease in the future, sometimes years later. However, there is uncertainty about how often reactivation of latent tuberculosis infection (LTBI) occurs. We searched eight databases (inception to June 25, 2019) to identify studies that quantified tuberculosis reactivation rates occurring more than 2 years after infection (late reactivation), with a focus on identifying untreated study cohorts with defined timing of LTBI acquisition (PROSPERO registered: CRD42017070594). We included 110 studies, divided into four methodological groups. Group 1 included studies that documented late reactivation rates from conversion (n=14) and group 2 documented late reactivation rates in LTBI cohorts from exposure (n=11). Group 3 included 86 studies in LTBI cohorts with an unknown exposure history, and group 4 included seven ecological studies. Since antibiotics have been used to treat tuberculosis, only 11 studies have documented late reactivation rates in infected, untreated cohorts from either conversion (group 1) or exposure (group 2); six of these studies lasted at least 4 years and none lasted longer than 10 years. These studies found that tuberculosis rates declined over time, reaching approximately 200 cases per 100 000 person-years or less by the fifth year, and possibly declining further after 5 years but interpretation was limited by decreasing or unspecified cohort sizes. In cohorts with latent tuberculosis and an unknown exposure history (group 3), tuberculosis rates were generally lower than those seen in groups 1 and 2, and beyond 10 years after screening, rates had declined to less than 100 per 100 000 person-years. Reinfection risks limit interpretation in all studies and the effect of age is unclear. Late reactivation rates are commonly estimated or modelled to prioritise tuberculosis control strategies towards tubuculosis elimination, but significant gaps remain in our understanding that must be acknowledged; the relative importance of late reactivation versus early progression to the global burden of tuberculosis remains unknown.

Estimating Long-term Tuberculosis Reactivation Rates in Australian Migrants

BACKGROUND

The risk of progression to tuberculosis (TB) disease is greatest soon after infection, yet disease may occur many years or decades later. However, rates of TB reactivation long after infection remain poorly quantified. Australia has a low incidence of TB and most cases occur among migrants. We explored how TB rates in Australian migrants varied with time from migration, age, and gender.

METHODS

We combined TB notifications in census years 2006, 2011, and 2016 with time- and country-specific estimates of latent TB prevalences in migrant cohorts to quantify postmigration reactivation rates.

RESULTS

During the census years, 3246 TB cases occurred among an estimated 2 084 000 migrants with latent TB. There were consistent trends in postmigration reactivation rates, which appeared to be dependent on both time from migration and age. Rates were lower in cohorts with increasing time, until at least 20 years from migration, and on this background there also appeared to be increasing rates during youth (15-24 years of age) and in those aged 70 years and above. Within 5 years of migration, annual reactivation rates were approximately 400 per 100 000 (uncertainty interval [UI] 320-480), dropping to 170 (UI 130-220) from 5 to 10 years and 110 (UI 70-160) from 10 to 20 years, then sustaining at 60-70 per 100 000 up to 60 years from migration. Rates varied depending on age at migration.

CONCLUSIONS

Postmigration reactivation rates appeared to show dependency on both time from migration and age. This approach to quantifying reactivation risks will enable evaluations of the potential impacts of TB control and elimination strategies.

Modelling insights into the COVID-19 pandemic

Coronavirus disease 2019 (COVID-19) is a newly emerged infectious disease caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) that was declared a pandemic by the World Health Organization on 11th March, 2020. Response to this ongoing pandemic requires extensive collaboration across the scientific community in an attempt to contain its impact and limit further transmission. Mathematical modelling has been at the forefront of these response efforts by: (1) providing initial estimates of the SARS-CoV-2 reproduction rate, R0 (of approximately 2-3); (2) updating these estimates following the implementation of various interventions (with significantly reduced, often sub-critical, transmission rates); (3) assessing the potential for global spread before significant case numbers had been reported internationally; and (4) quantifying the expected disease severity and burden of COVID-19, indicating that the likely true infection rate is often orders of magnitude greater than estimates based on confirmed case counts alone. In this review, we highlight the critical role played by mathematical modelling to understand COVID-19 thus far, the challenges posed by data availability and uncertainty, and the continuing utility of modelling-based approaches to guide decision making and inform the public health response. †Unless otherwise stated, all bracketed error margins correspond to the 95% credible interval (CrI) for reported estimates.

Role of modelling in COVID-19 policy development

Models have played an important role in policy development to address the COVID-19 outbreak from its emergence in China to the current global pandemic. Early projections of international spread influenced travel restrictions and border closures. Model projections based on the virus's infectiousness demonstrated its pandemic potential, which guided the global response to and prepared countries for increases in hospitalisations and deaths. Tracking the impact of distancing and movement policies and behaviour changes has been critical in evaluating these decisions. Models have provided insights into the epidemiological differences between higher and lower income countries, as well as vulnerable population groups within countries to help design fit-for-purpose policies. Economic evaluation and policies have combined epidemic models and traditional economic models to address the economic consequences of COVID-19, which have informed policy calls for easing restrictions. Social contact and mobility models have allowed evaluation of the pathways to safely relax mobility restrictions and distancing measures. Finally, models can consider future end-game scenarios, including how suppression can be achieved and the impact of different vaccination strategies.

The Importance of Heterogeneity to the Epidemiology of Tuberculosis

Although less well-recognized than for other infectious diseases, heterogeneity is a defining feature of tuberculosis (TB) epidemiology. To advance toward TB elimination, this heterogeneity must be better understood and addressed. Drivers of heterogeneity in TB epidemiology act at the level of the infectious host, organism, susceptible host, environment, and distal determinants. These effects may be amplified by social mixing patterns, while the variable latent period between infection and disease may mask heterogeneity in transmission. Reliance on notified cases may lead to misidentification of the most affected groups, as case detection is often poorest where prevalence is highest. Assuming that average rates apply across diverse groups and ignoring the effects of cohort selection may result in misunderstanding of the epidemic and the anticipated effects of control measures. Given this substantial heterogeneity, interventions targeting high-risk groups based on location, social determinants, or comorbidities could improve efficiency, but raise ethical and equity considerations.

Cost-effectiveness of 3 months of weekly rifapentine and isoniazid compared with other standard treatment regimens for latent tuberculosis infection: a decision analysis study

Background

Latent tuberculosis infection (LTBI) is a critical driver of the global burden of active TB, and therefore LTBI treatment is key for TB elimination. Treatment regimens for LTBI include self-administered daily isoniazid for 6 (6H) or 9 (9H) months, self-administered daily rifampicin plus isoniazid for 3 months (3RH), self-administered daily rifampicin for 4 months (4R) and weekly rifapentine plus isoniazid for 3 months self-administered (3HP-SAT) or administered by a healthcare worker as directly observed therapy (3HP-DOT). Data on the relative cost-effectiveness of these regimens are needed to assist policymakers and clinicians in selecting an LTBI regimen.

Objectives

To evaluate the cost-effectiveness of all regimens for treating LTBI.

Methods

We developed a Markov model to investigate the cost-effectiveness of 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H for LTBI treatment in a cohort of 10000 adults with LTBI. Cost-effectiveness was evaluated from a health system perspective over a 20 year time horizon.

Results

Compared with no preventive treatment, 3HP-DOT, 3HP-SAT, 4R, 3RH, 9H and 6H prevented 496, 470, 442, 418, 370 and 276 additional cases of active TB per 10000 patients, respectively. All regimens reduced costs and increased QALYs compared with no preventive treatment. 3HP was more cost-effective under DOT than under SAT at a cost of US$27948 per QALY gained.

Conclusions

Three months of weekly rifapentine plus isoniazid is more cost-effective than other regimens. Greater recognition of the benefits of short-course regimens can contribute to the scale-up of prevention and achieving the 'End TB' targets.

Profiling Mycobacterium tuberculosis transmission and the resulting disease burden in the five highest tuberculosis burden countries

BACKGROUND

Tuberculosis (TB) control efforts are hampered by an imperfect understanding of TB epidemiology. The true age distribution of disease is unknown because a large proportion of individuals with active TB remain undetected. Understanding of transmission is limited by the asymptomatic nature of latent infection and the pathogen's capacity for late reactivation. A better understanding of TB epidemiology is critically needed to ensure effective use of existing and future control tools.

METHODS

We use an agent-based model to simulate TB epidemiology in the five highest TB burden countries-India, Indonesia, China, the Philippines and Pakistan-providing unique insights into patterns of transmission and disease. Our model replicates demographically realistic populations, explicitly capturing social contacts between individuals based on local estimates of age-specific contact in household, school and workplace settings. Time-varying programmatic parameters are incorporated to account for the local history of TB control.

RESULTS

We estimate that the 15-19-year-old age group is involved in more than 20% of transmission events in India, Indonesia, the Philippines and Pakistan, despite representing only 5% of the local TB incidence. According to our model, childhood TB represents around one fifth of the incident TB cases in these four countries. In China, three quarters of incident TB were estimated to occur in the ≥ 45-year-old population. The calibrated per-contact transmission risk was found to be similar in each of the five countries despite their very different TB burdens.

CONCLUSIONS

Adolescents and young adults are a major driver of TB in high-incidence settings. Relying only on the observed distribution of disease to understand the age profile of transmission is potentially misleading.

Hyper transmission of Beijing lineage Mycobacterium tuberculosis: Systematic review and meta-analysis

OBJECTIVES

The globally distributed "Beijing" lineage of Mycobacterium tuberculosis has been associated with outbreaks worldwide. Laboratory based studies have suggested that Beijing lineage may have increased fitness; however, it has not been established whether these differences are of epidemiological significance with regards to transmission. Therefore, we undertook a systematic review of epidemiological studies of tuberculosis clustering to compare the transmission dynamics of Beijing lineages versus the non-Beijing lineages.

METHODS

We systematically searched Embase and MEDLINE before 31st December 2018, for studies which provided information on the transmission dynamics of the different M. tuberculosis lineages. We included articles that conducted population-based cross-sectional or longitudinal molecular epidemiological studies reporting information about extent of transmission of different lineages. The protocol for this systematic review was prospectively registered with PROSPERO (CDR42018088579).

RESULTS

Of 2855 records identified by the search, 46 were included in the review, containing 42,700 patients from 27 countries. Beijing lineage was the most prevalent and highly clustered strain in 72.4% of the studies and had a higher likelihood of transmission than non-Beijing lineages (OR 1·81 [95% 1·28-2·57], I² = 94·0%, τ² = 0·59, p < 0·01).

CONCLUSIONS

Despite considerable heterogeneity across epidemiological contexts, Beijing lineage appears to be more transmissible than other lineages.

Mycobacterium tuberculosis: Active disease and latent infection in a renal transplant cohort

AIM

Our aim was threefold: first, to determine the incidence of active TB in our cohort, second to investigate the risk factors for active TB and third, to understand current screening practices. The ultimate goal was to use our findings to inform development of local and national guidelines.

METHODS

The records of all adult patients who underwent renal transplantation at our centre from 2005 to 2014 were retrospectively reviewed to assess current screening practices, the risks for and burden of active TB.

RESULTS

A total of 660 individuals underwent renal transplantation during this period, totalling 3647 person years of follow up. Two patients were diagnosed with active TB after renal transplant, resulting in an incidence of 55 per 100 000 person-years. Of 656 transplant recipients, 102 (15.5%) were born in high TB incidence countries and 89 (13.5%) had an interferon gamma release assay (IGRA) at any point. Individuals born in high TB risk countries had a much higher incidence of active TB (353 per 100 000 person-years). Ten individuals had positive IGRA tests, of whom two were treated for active TB, two received chemoprophylaxis and six were not treated.

CONCLUSIONS

In the absence of formal guidelines, IGRA-based screening for LTBI was infrequently performed. Our data suggest that screening and treatment of renal transplant recipients born in high incidence countries is an important preventive measure.

The role of super-spreading events in Mycobacterium tuberculosis transmission: evidence from contact tracing

BACKGROUND

In current epidemiology of tuberculosis (TB), heterogeneity in infectiousness among TB patients is a challenge, which is not well studied. We aimed to quantify this heterogeneity and the presence of "super-spreading" events that can assist in designing optimal public health interventions.

METHODS

TB epidemiologic investigation data notified between 1 January 2005 and 31 December 2015 from Victoria, Australia were used to quantify TB patients' heterogeneity in infectiousness and super-spreading events. We fitted a negative binomial offspring distribution (NBD) for the number of secondary infections and secondary active TB disease each TB patient produced. The dispersion parameter, k, of the NBD measures the level of heterogeneity, where low values of k (e.g. k < 1) indicate over-dispersion. Super-spreading was defined as patients causing as many or more secondary infections as the 99th centile of an equivalent homogeneous distribution. Contact infection was determined based on a tuberculin skin test (TST) result of ≥10 mm. A NBD model was fitted to identify index characteristics that were associated with the number of contacts infected and risk ratios (RRs) were used to quantify the strength of this association.

RESULTS

There were 4190 (2312 pulmonary and 1878 extrapulmonary) index TB patients and 18,030 contacts. A total of 15,522 contacts were tested with TST, of whom 3213 had a result of ≥10 mm. The dispersion parameter, k for secondary infections was estimated at 0.16 (95%CI 0.14-0.17) and there were 414 (9.9%) super-spreading events. From the 3213 secondary infections, 2415 (75.2%) were due to super-spreading events. There were 226 contacts who developed active TB disease and a higher level of heterogeneity was found for this outcome than for secondary infection, with k estimated at 0.036 (95%CI 0.025-0.046). In regression analyses, we found that infectiousness was greater among index patients found by clinical presentation and those with bacteriological confirmation.

CONCLUSION

TB transmission is highly over dispersed and super-spreading events are responsible for a substantial majority of secondary infections. Heterogeneity of transmission and super-spreading are critical issues to consider in the design of interventions and models of TB transmission dynamics.

The cost-effectiveness of canakinumab for secondary prevention of cardiovascular disease: The Australian healthcare perspective

BACKGROUND

Canakinumab is a fully human monoclonal antibody targeting interleukin-1β. It is currently indicated for use in those with rheumatologic disorders due to its anti-inflammatory properties, and was recently shown to be beneficial for the secondary prevention of cardiovascular disease (CVD). However, the cost-effectiveness of canakinumab used to treat CVD is unknown.

METHODS

A Markov state transition model was developed and populated with a hypothetical sample of 1000 individuals profiled on the Canakinumab Antiinflammatory Thrombosis Outcome Study (CANTOS); with a history of myocardial infarction (MI) and blood concentrations of high-sensitivity C-reactive protein (hsCRP) of >2 mg/L. With each annual cycle, individuals could have a recurrent non-fatal CVD event (MI or stroke), or die from a CVD event or die from other causes based on data from CANTOS. Individuals continued to cycle through the model for 20 years or until death. Cost and utility data was applied. Outcomes were discounted (5% annually).

RESULTS

Over a 20-year time horizon, canakinumab is predicted to prevent 40 recurrent cardiovascular events and save 287 (discounted) years of life and 239 (discounted) quality-adjusted life years (QALYs) in 1000 individuals. At an annual cost of AUD36,049 (USD25,590, GBP19,662) per person, canakinumab would not be considered cost-effective within the Australian healthcare system, with an incremental cost-effectiveness ratio (ICER) of AUD1,221,170 per QALY gained.

CONCLUSIONS

Canakinumab is an attractive treatment option to reduce recurrent CVD among patients with high hsCRP. It would be considered cost-effective in this treatment setting within the perspective of the Australian public healthcare system if its annual costs do not exceed AUD1500 (USD1065, GBP818) per person.

Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

BACKGROUND

Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden.

METHODS

We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO ( CRD42016036655 ).

RESULTS

We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined.

CONCLUSIONS

A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control.

The role of geospatial hotspots in the spatial spread of tuberculosis in rural Ethiopia: a mathematical model

Geospatial tuberculosis (TB) hotspots are hubs of TB transmission both within and across community groups. We aimed to quantify the extent to which these hotspots account for the spatial spread of TB in a high-burden setting. We developed spatially coupled models to quantify the spread of TB from geographical hotspots to distant regions in rural Ethiopia. The population was divided into three 'patches' based on their proximity to transmission hotspots, namely hotspots, adjacent regions and remote regions. The models were fitted to 5-year notification data aggregated by the metapopulation structure. Model fitting was achieved with a Metropolis-Hastings algorithm using a Poisson likelihood to compare model-estimated notification rate with observed notification rates. A cross-coupled metapopulation model with assortative mixing by region closely fit to notification data as assessed by the deviance information criterion. We estimated 45 hotspot-to-adjacent regions transmission events and 2 hotspot-to-remote regions transmission events occurred for every 1000 hotspot-to-hotspot transmission events. Although the degree of spatial coupling was weak, the proportion of infections in the adjacent region that resulted from mixing with hotspots was high due to the high prevalence of TB cases in a hotspot region, with approximately 75% of infections attributable to hotspot contact. Our results suggest that the role of hotspots in the geospatial spread of TB in rural Ethiopia is limited, implying that TB transmission is primarily locally driven.

Agent-based models of malaria transmission: a systematic review

BACKGROUND

Much of the extensive research regarding transmission of malaria is underpinned by mathematical modelling. Compartmental models, which focus on interactions and transitions between population strata, have been a mainstay of such modelling for more than a century. However, modellers are increasingly adopting agent-based approaches, which model hosts, vectors and/or their interactions on an individual level. One reason for the increasing popularity of such models is their potential to provide enhanced realism by allowing system-level behaviours to emerge as a consequence of accumulated individual-level interactions, as occurs in real populations.

METHODS

A systematic review of 90 articles published between 1998 and May 2018 was performed, characterizing agent-based models (ABMs) relevant to malaria transmission. The review provides an overview of approaches used to date, determines the advantages of these approaches, and proposes ideas for progressing the field.

RESULTS

The rationale for ABM use over other modelling approaches centres around three points: the need to accurately represent increased stochasticity in low-transmission settings; the benefits of high-resolution spatial simulations; and heterogeneities in drug and vaccine efficacies due to individual patient characteristics. The success of these approaches provides avenues for further exploration of agent-based techniques for modelling malaria transmission. Potential extensions include varying elimination strategies across spatial landscapes, extending the size of spatial models, incorporating human movement dynamics, and developing increasingly comprehensive parameter estimation and optimization techniques.

CONCLUSION

Collectively, the literature covers an extensive array of topics, including the full spectrum of transmission and intervention regimes. Bringing these elements together under a common framework may enhance knowledge of, and guide policies towards, malaria elimination. However, because of the diversity of available models, endorsing a standardized approach to ABM implementation may not be possible. Instead it is recommended that model frameworks be contextually appropriate and sufficiently described. One key recommendation is to develop enhanced parameter estimation and optimization techniques. Extensions of current techniques will provide the robust results required to enhance current elimination efforts.

Heterogeneity of distribution of tuberculosis in Sheka Zone, Ethiopia: drivers and temporal trends

OBJECTIVE

To describe the distribution of tuberculosis (TB) and its drivers in Sheka Zone, a geographically remote region of Ethiopia.

METHODS

We collected data on TB patients treated from 2010 to 2014 in the Sheka Zone. Predictors of TB incidence were determined using a multivariate generalised linear regression model.

RESULTS

We found significant spatial autocorrelation of TB incidence by kebele (the smallest administrative geographical subdivision in Ethiopia) (Moran's I = 0.3, P < 0.001). The average TB incidence per kebele ranged from 0 to 453 per 100 000 population per year, and was significantly associated with average TB incidence across adjacent kebeles, TB incidence in the same kebele in the previous year and health facility availability. Each increment in TB incidence by 10/100 000/year in adjacent kebeles or in a previous year was associated with an increase in TB incidence of respectively 3.0 and 5.5/100 000/year. Availability of a health centre was associated with an increase in TB incidence of 84.3/100 000.

CONCLUSIONS

TB incidence in rural Ethiopia is highly heterogeneous, showing significant spatial autocorrelation. Both local transmission and access to health care are likely contributors to this pattern. Identification of local hotspots may assist in developing and optimising effective prevention and control strategies.

Is IPT more effective in high-burden settings? Modelling the effect of tuberculosis incidence on IPT impact

SETTING

Isoniazid preventive therapy (IPT) is effective for preventing active tuberculosis (TB), although its mechanism of action is poorly understood and the optimal disease burden for IPT use has not been defined.

OBJECTIVE

To describe the relationship between TB incidence and IPT effectiveness.

METHODS

We constructed a model of TB transmission dynamics to investigate IPT effectiveness under various epidemiological settings. The model structure was intended to be highly adaptable to uncertainty in both input parameters and the mechanism of action of IPT. To determine the optimal setting for IPT use, we identified the lowest number needed to treat (NNT) with IPT to prevent one case of active TB.

RESULTS

We found that the NNT as a function of TB incidence shows a 'U-shape', whereby IPT impact is greatest at an intermediate incidence and attenuated at both lower and higher incidence levels. This U-shape was observed over a broad range of parameter values; the optimal TB incidence was between 500 and 900 cases per 100 000 per year.

CONCLUSIONS

TB burden is a critical factor to consider when making decisions about communitywide implementation of IPT. We believe that the total disease burden should not preclude programmatic application of IPT.

Recurrence of tuberculosis in a low-incidence setting without directly observed treatment: Victoria, Australia, 2002-2014

SETTING

Victoria, Australia, is an industrialised setting with low tuberculosis (TB) incidence and universal health care. Individually tailored adherence support for self-administered daily anti-tuberculosis treatment is provided. Directly observed treatment (DOT) is very rarely used.

OBJECTIVE

To review the rate of recurrent TB in Victoria between 2002 and 2014.

DESIGN

This was a retrospective cohort study. All recurrent episodes of TB were reviewed and 24-locus MIRU-VNTR (mycobacterial interspersed repetitive units-variable number of tandem repeats) molecular typing was used where possible to determine the likelihood of relapse or reinfection.

RESULTS

Of 4766 notifications, 32 (0.7%) were recurrent episodes. Of 20 episodes that occurred in patients who had previously completed treatment, 11 were culture-positive (0.4% of 3012 culture-positive episodes): 9 were likely relapses (distinguishable at no more than one of 24 loci) and two were likely reinfections, giving a TB relapse rate among culture-positive episodes of 52.5/100 000 person-years (mean time to study end per patient of 5.7 years). The median time until relapse was 18 months (interquartile range 12-30).

CONCLUSIONS

The low rate of relapse in our setting demonstrates that individually tailored adherence support for self-administered anti-tuberculosis treatment can achieve excellent treatment outcomes.

Coupled, multi-strain epidemic models of mutating pathogens

We introduce and analyze coupled, multi-strain epidemic models designed to simulate the emergence and dissemination of mutant (e.g. drug-resistant) pathogen strains. In particular, we investigate the mathematical and biological properties of a general class of multi-strain epidemic models in which the infectious compartments of each strain are coupled together in a general manner. We derive explicit expressions for the basic reproduction number of each strain and highlight their importance in regulating the system dynamics (e.g. the potential for an epidemic outbreak) and the existence of nonnegative endemic solutions. Importantly, we find that the basic reproduction number of each strain is independent of the mutation rates between the strains - even under quite general assumptions for the form of the infectious compartment coupling. Moreover, we verify that the coupling term promotes strain coexistence (as an extension of the competitive exclusion principle) and demonstrate that the strain with the greatest reproductive capacity is not necessarily the most prevalent. Finally, we briefly discuss the implications of our results for public health policy and planning.

A novel Bayesian geospatial method for estimating tuberculosis incidence reveals many missed TB cases in Ethiopia

Background

Reported tuberculosis (TB) incidence globally continues to be heavily influenced by expert opinion of case detection rates and ecological estimates of disease duration. Both approaches are recognised as having substantial variability and inaccuracy, leading to uncertainty in true TB incidence and other such derived statistics.

Methods

We developed Bayesian binomial mixture geospatial models to estimate TB incidence and case detection rate (CDR) in Ethiopia. In these models the underlying true incidence was formulated as a partially observed Markovian process following a mixed Poisson distribution and the detected (observed) TB cases as a binomial distribution, conditional on CDR and true incidence. The models use notification data from multiple areas over several years and account for the existence of undetected TB cases and variability in true underlying incidence and CDR. Deviance information criteria (DIC) were used to select the best performing model.

Results

A geospatial model was the best fitting approach. This model estimated that TB incidence in Sheka Zone increased from 198 (95% Credible Interval (CrI) 187, 233) per 100,000 population in 2010 to 232 (95% CrI 212, 253) per 100,000 population in 2014. The model revealed a wide discrepancy between the estimated incidence rate and notification rate, with the estimated incidence ranging from 1.4 (in 2014) to 1.7 (in 2010) times the notification rate (CDR of 71% and 60% respectively). Population density and TB incidence in neighbouring locations (spatial lag) predicted the underlying TB incidence, while health facility availability predicted higher CDR.

Conclusion

Our model estimated trends in underlying TB incidence while accounting for undetected cases and revealed significant discrepancies between incidence and notification rates in rural Ethiopia. This approach provides an alternative approach to estimating incidence, entirely independent of the methods involved in current estimates and is feasible to perform from routinely collected surveillance data.

Electronic supplementary material

The online version of this article (10.1186/s12879-017-2759-0) contains supplementary material, which is available to authorized users.