Agent-based modelling of Mycobacterium tuberculosis transmission: a systematic review.

Background: Traditional epidemiological models tend to oversimplify the transmission dynamics of Mycobacterium tuberculosis (M.tb) to replicate observed tuberculosis (TB) epidemic patterns. This has led to growing interest in advanced methodologies like agent-based modelling (ABM), which can more accurately represent the complex heterogeneity of TB transmission.

A data science pipeline applied to Australia's 2022 COVID-19 Omicron waves.

The field of software engineering is advancing at astonishing speed, with packages now available to support many stages of data science pipelines. These packages can support infectious disease modelling to be more robust, efficient and transparent, which has been particularly important during the COVID-19 pandemic. We developed a package for the construction of infectious disease models, integrated it with several open-source libraries and applied this composite pipeline to multiple data sources that provided insights into Australia's 2022 COVID-19 epidemic.

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.

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.

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.

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.

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.

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.

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 ( ) 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.

Vaccines and variants: Modelling insights into emerging issues in COVID-19 epidemiology.

Mathematical modelling has played a pivotal role in understanding the epidemiology of and guiding public health responses to the ongoing coronavirus disease of 2019 (COVID-19) pandemic. Here, we review the role of epidemiological models in understanding evolving epidemic characteristics, including the effects of vaccination and Variants of Concern (VoC). We highlight ways in which models continue to provide important insights, including (1) calculating the herd immunity threshold and evaluating its limitations; (2) verifying that nascent vaccines can prevent severe disease, infection, and transmission but may be less efficacious against VoC; (3) determining optimal vaccine allocation strategies under efficacy and supply constraints; and (4) determining that VoC are more transmissible and lethal than previously circulating strains, and that immune escape may jeopardize vaccine-induced herd immunity.

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.

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).

Ethics of selective restriction of liberty in a pandemic.

Liberty-restricting measures have been implemented for centuries to limit the spread of infectious diseases. This article considers if and when it may be ethically acceptable to impose selective liberty-restricting measures in order to reduce the negative impacts of a pandemic by preventing particularly vulnerable groups of the community from contracting the disease. We argue that the commonly accepted explanation-that liberty restrictions may be justified to prevent harm to others when this is the least restrictive option-fails to adequately accommodate the complexity of the issue or the difficult choices that must be made, as illustrated by the COVID-19 pandemic.

Timing of 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.

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.

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.

Heterogeneous infectiousness in mathematical models of tuberculosis: A systematic review.

TB mathematical models employ various assumptions and approaches in dealing with the heterogeneous infectiousness of persons with active TB. We reviewed existing approaches and considered the relationship between them and existing epidemiological evidence. We searched the following electronic bibliographic databases from inception to 9 October 2018: MEDLINE, EMBASE, Biosis, Global Health and Scopus.

Strategic Planning for Tuberculosis Control in the Republic of Fiji.

The tuberculosis (TB) health burden in Fiji has been declining in recent years, although challenges remain in improving control of the diabetes co-epidemic and achieving adequate case detection across the widely dispersed archipelago. We applied a mathematical model of TB transmission to the TB epidemic in Fiji that captured the historical reality over several decades, including age stratification, diabetes, varying disease manifestations, and incorrect diagnoses. Next, we simulated six intervention scenarios that are under consideration by the Fiji National Tuberculosis Program.

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.

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.