Modelling the impact of timelines of testing and isolation on disease control

Testing and isolation remain a key component of public health responses to both persistent and emerging infectious diseases.Although the value of these measures have been demonstrated in combating recent outbreaks including the COVID-19 pandemic and monkeypox,their impact depends critically on the timelines of testing and start of isolation during the course of disease.To investigate this impact,we developed a delay differential model and incorporated age-since-symptom-onset as a parameter for delay in testing.We then used the model to compare the outcomes of reverse-transcription polymerase chain reaction(RT-PCR)and rapid antigen(RA)testing methods when isolation starts either at the time of testing or at the time of test result.Parameterizing the model with estimates of SARS-CoV-2 infection and diagnostic sensitivity of the tests,we found that the reduction of disease transmission using the RA test can be comparable to that achieved by applying the RT-PCR test.Given constraints and inevitable delays associated with sample collection and laboratory assays in RT-PCR testing post symptom onset,self-administered RA tests with short turnaround times present a viable alternative for timely isolation of infectious cases.

Relatedness of the incidence decay with exponential adjustment(IDEA)model,“Farr's law”and SIR compartmental difference equation models

Mathematical models are often regarded as recent innovations in the description and analysis of infectious disease outbreaks and epidemics,but simple mathematical expressions have been in use for projection of epidemic trajectories for more than a century.We recently introduced a single equation model(the incidence decay with exponential adjustment,or IDEA model)that can be used for short-term epidemiological forecasting.In the mid-19th century,Dr.William Farr made the observation that epidemic events rise and fall in a roughly symmetrical pattern that can be approximated by a bell-shaped curve.He noticed that this time-evolution behavior could be captured by a single mathematical formula(“Farr's law”)that could be used for epidemic forecasting.We show here that the IDEA model follows Farr's law,and show that for intuitive assumptions,Farr's Law can be derived from the IDEA model.Moreover,we show that both mathematical approaches,Farr's Law and the IDEA model,resemble solutions of a susceptible-infectious-removed(SIR)compartmental differential-equation model in an asymptotic limit,where the changes of disease transmission respond to control measures,and not only to the depletion of susceptible individuals.This suggests that the concept of the reproduction number eR 0T was implicitly captured in Farr's(pre-microbial era)work,and also suggests that control of epidemics,whether via behavior change or intervention,is as integral to the natural history of epidemics as is the dynamics of disease transmission.

Evaluation of TB elimination strategies in Canadian Inuit populations:Nunavut as a case study

Tuberculosis(TB)continues to disproportionately affect Inuit populations in Canada with some communities having over 300 times higher rate of active TB than Canadian-born,non-Indigenous people.Inuit Tuberculosis Elimination Framework has set the goal of reducing active TB incidence by at least 50%by 2025,aiming to eliminate it by 2030.Whether these goals are achievable with available resources and treatment regimens currently in practice has not been evaluated.We developed an agent-based model of TB transmission to evaluate timelines and milestones attainable in Nunavut,Canada by including case findings,contact-tracing and testing,treatment of latent TB infection(LTBI),and the government investment on housing infrastructure to reduce the average house-hold size.The model was calibrated to ten years of TB incidence data,and simulated for 20 years to project program outcomes.We found that,under a range of plausible scenarios with tracing and testing of 25%e100%of frequent contacts of detected active cases,the goal of 50%reduction in annual incidence by 2025 is not achievable.If active TB cases are identified rapidly within one week of becoming symptomatic,then the annual incidence would reduce below 100 per 100,000 population,with 50%reduction being met between 2025 and 2030.Eliminating TB from Inuit populations would require high rates of contacttracing and would extend beyond 2030.The findings indicate that time-to-identification of active TB is a critical factor determining program effectiveness,suggesting that investment in resources for rapid case detection is fundamental to controlling TB.