Estimating the incidence and diagnosed proportion of HIV infections in Japan: a statistical modeling study

Abstract

BackgroundEpidemiological surveillance of HIV infection in Japan involves two technical problems for directly applying a classical backcalculation method, i.e., (i) all AIDS cases are not counted over time and (ii) people diagnosed with HIV have received antiretroviral therapy, extending the incubation period. The present study aimed to address these issues and estimate the HIV incidence and the proportion of diagnosed HIV infections, using a simple statistical model.MethodsFrom among Japanese nationals, yearly incidence data of HIV diagnoses and patients with AIDS who had not previously been diagnosed as HIV positive, from 1985 to 2017, were analyzed. Using the McKendrick partial differential equation, general convolution-like equations were derived, allowing estimation of the HIV incidence and the time-dependent rate of diagnosis. A likelihood-based approach was used to obtain parameter estimates.ResultsAssuming that the median incubation period was 10.0 years, the cumulative number of HIV infections was estimated to be 29,613 (95% confidence interval (CI): 29,059, 30,167) by the end of 2017, and the proportion of diagnosed HIV infections was estimated at 80.3% (95% CI [78.7%–82.0%]). Allowing the median incubation period to range from 7.5 to 12.3 years, the estimate of the proportion diagnosed can vary from 77% to 84%.DiscussionThe proportion of diagnosed HIV infections appears to have not yet reached 90% among Japanese nationals. Compared with the peak incidence from 2005–2008, new HIV infections have clearly been in a declining trend; however, there are still more than 1,000 new HIV infections per year in Japan. To increase the diagnosed proportion of HIV infections, it is critical to identify people who have difficulty accessing consultation, testing, and care, and to explore heterogeneous patterns of infection.

Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess

“…One of the critical issues in infectious disease epidemiology is that the time of infection event is seldom directly observable. For this reason, the time of infection needs to be statistically estimated, employing a backcalculation method [2]. Using a sophisticated statistical model with doubly interval-censored likelihood and right truncation with an exponential growth of cases, the mean incubation period has been estimated to be about 5.0 days [3].…”

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“…The second component, f late , models HIV transmission during the asymptomatic stage and the disease stage (after progression to Acquired Immune Deficiency Syndrome (AIDS)). We assume that f late (τ ) has a mean of 10 years (Brookmeyer and Goedert, 1989;Nishiura, 2019) and a shape parameter of 2 (to roughly match the wide generationinterval distribution of HIV (Fraser et al, 2004)). Finally, p early is the proportion of early HIV transmission.…”

Modeling methods for estimating HIV incidence: a mathematical review

“…Adding information on HIV diagnoses to the back-calculation method enables estimation of HIV incidence in recent years and reduces the uncertainty associated with this estimate to some degree. Moreover, the method enables joint estimation of HIV diagnosis rate [44]. However, challenges associated with estimating or assuming a time from infection to HIV diagnosis remain.…”