Modeling methods for estimating HIV incidence: a mathematical review

Analysing HCV incidence trends in people who inject drugs using serial behavioural and seroprevalence data: A modelling study

INTRODUCTION

The introduction of new direct-acting antivirals for hepatitis C virus (HCV) infection, has enabled the formulation of a HCV elimination strategy led by the World Health Organisation (WHO). Guidelines for elimination of HCV target a reduction in incidence, but this is difficult to measure and needs estimating.

METHODS

Serial cross-sectional bio-behavioural sero-surveys provide information on an individual's infection status and duration of exposure and how these change over time. These data can be used to estimate the rate of first infection through appropriate statistical models. This study utilised updated HCV seroprevalence information from the Unlinked Anonymous Monitoring survey, an annual survey of England, Wales and Northern Ireland monitoring the prevalence of blood borne viruses in people who inject drugs. Flexible parametric and semiparametric approaches, including fractional polynomials and splines, for estimating incidence rates by exposure time and survey year were implemented and compared.

RESULTS

Incidence rates were shown to peak in those recently initiating injecting drug use at approximately 0.20 infections per person-year followed by a rapid reduction in the subsequent few years of injecting to approximately 0.05 infections per person-year. There was evidence of a rise in incidence rates for recent initiates between 2011 and 2020 from 0.17 infections per person-year (95 % CI, 0.16-0.19) to 0.26 infections per person-year (0.23-0.30). In those injecting for longer durations, incidence rates were stable over time.

CONCLUSIONS

Fractional polynomials provided an adequate fit with relatively few parameters, but splines may be preferable to ensure flexibility, in particular, to detect short-term changes in the rate of first infection over time that may be a result of treatment effects. Although chronic HCV prevalence has declined with treatment scale up over 2016-2020, there is no evidence yet of a corresponding fall in the rate of first infection. Seroprevalence and risk behaviour data can be used to estimate and monitor HCV incidence, providing insight into progress towards WHO defined elimination of HCV.

Estimating HIV incidence over a decade in Zimbabwe: A comparison of the catalytic and Farrington models

Over the years, numerous modelling studies have been proposed to estimate HIV incidence. As a result, this study aimed to evaluate two alternative methods for predicting HIV incidence in Zimbabwe between 2005 and 2015. We estimated HIV incidence from seroprevalence data using the catalytic and Farrington-2-parameter models. Data were obtained from 2005-06, 2010-11, and 2015 Zimbabwe Demographic Health Survey (ZDHS). These models were validated at the micro and macro-level using community-based cohort incidence and empirical estimates from UNAIDS EPP/SPECTRUM, respectively. The HIV incidence for the catalytic model was 0.32% (CI: 0.28%, 0.36%), 0.36% (CI: 0.33%, 0.39%), and 0.28% (CI: 0.26%, 0.30%), for the years 2005-06, 2010-11, and 2015, respectively. The HIV incidence for the Farrington model was 0.21% (CI: 0.16%, 0.26%), 0.22% (CI: 0.20%, 0.25%), and 0.19% (CI: 0.16%, 0.22%), for the years 2005-06, 2010-11, and 2015, respectively. According to these findings, the catalytic model estimated a higher HIV incidence rate than the Farrington model. Compared to cohort estimates, the estimates were within the observed 95% confidence interval, with 88% and 75% agreement for the catalytic and Farrington models, respectively. The limits of agreement observed in the Bland-Altman plot were narrow for all plots, indicating that our model estimates were comparable to cohort estimates. Compared to UNAIDS estimates, the catalytic model predicted a progressive increase in HIV incidence for males throughout all survey years. Without a doubt, HIV incidence declined with each subsequent survey year for all models. To improve programmatic and policy decisions in the national HIV response, we recommend the triangulation of multiple methods for incidence estimation and interpretation of results. Multiple estimating approaches should be considered to reduce uncertainty in the estimations from various models.

Identification of Key Components in Health System Using System Thinking Approach: A Scoping Review

Background

The dynamic and systemic planning and targeting in the health system require attention to all the system's components and investigation of their causal relationship in order to form a clear view and image of it. Therefore, the present study was designed with the aim of identifying the comprehensive dimensions of the system within a specific framework.

Methods

Key components in the health system were identified through the scoping review method. For this purpose, 61 studies with selected keywords were extracted from international databases, including Scopus, Web of Science, PubMed and Embase, and Persian language databases including Magiran and SID. Inclusion and exclusion criteria in this study were languages, time range, repeated studies, studies related to the health system, appropriateness of studies with the subject and purpose of the present study and the method used. The content of the selected studies and extracted themes were analyzed and categorized in the Balanced Scorecard (BSC) framework.

Results

In health system analysis, key components were divided into 18 main categories and 45 categories. Also, they were categorized according to the BSC framework into five dimensions of population health, service delivery, growth and development, financing, and governance & leadership.

Conclusion

For health system improvement, policymakers and planners should consider these factors in a dynamic system and a causal network.

Early estimation of the number of hidden HIV infected subjects: An extended Kalman filter approach

In the last decades several epidemic emergencies have been affecting the world, influencing the social relationships, the economics and the habits. In particular, starting in the early '80, the Acquired Immunodeficiency Syndrome, AIDS, is representing one of the most worrying sanitary emergency, that has caused up to now more than 25 million of dead patients. The infection is caused by the Human Immunodeficiency Virus, HIV, that may be transmitted by body fluids; therefore with wise behaviours the epidemic spread could rapidly be contained. This sanitary emergency is peculiar for the long incubation time: it can reach even 10 years, a long period in which the individual can unconsciously infect other subjects. The identification of the number of infected unaware people, mandatory to define suitable containment measures, is here obtained by using the extended Kalman filter applied to a noisy model in which, reasonably, only the number of infected diagnosed patients is available. Numerical simulations and real data analysis support the effectiveness of the approach.

Impact of non-pharmaceutical interventions and vaccination on COVID-19 outbreaks in Nunavut, Canada: a Canadian Immunization Research Network (CIRN) study

Background

Nunavut, the northernmost Arctic territory of Canada, experienced three community outbreaks of the coronavirus disease 2019 (COVID-19) from early November 2020 to mid-June 2021. We sought to investigate how non-pharmaceutical interventions (NPIs) and vaccination affected the course of these outbreaks.

Methods

We used an agent-based model of disease transmission to simulate COVID-19 outbreaks in Nunavut. The model encapsulated demographics and household structure of the population, the effect of NPIs, and daily number of vaccine doses administered. We fitted the model to inferred, back-calculated infections from incidence data reported from October 2020 to June 2021. We then compared the fit of the scenario based on case count data with several counterfactual scenarios without the effect of NPIs, without vaccination, and with a hypothetical accelerated vaccination program whereby 98% of the vaccine supply was administered to eligible individuals.

Results

We found that, without a territory-wide lockdown during the first COVID-19 outbreak in November 2020, the peak of infections would have been 4.7 times higher with a total of 5,404 (95% CrI: 5,015—5,798) infections before the start of vaccination on January 6, 2021. Without effective NPIs, we estimated a total of 4,290 (95% CrI: 3,880—4,708) infections during the second outbreak under the pace of vaccination administered in Nunavut. In a hypothetical accelerated vaccine rollout, the total infections during the second Nunavut outbreak would have been 58% lower, to 1,812 (95% CrI: 1,593—2,039) infections. Vaccination was estimated to have the largest impact during the outbreak in April 2021, averting 15,196 (95% CrI: 14,798—15,591) infections if the disease had spread through Nunavut communities. Accelerated vaccination would have further reduced the total infections to 243 (95% CrI: 222—265) even in the absence of NPIs.

Conclusions

NPIs have been essential in mitigating pandemic outbreaks in this large, geographically distanced and remote territory. While vaccination has the greatest impact to prevent infection and severe outcomes, public health implementation of NPIs play an essential role in the short term before attaining high levels of immunity in the population.

Supplementary information

The online version contains supplementary material available at 10.1186/s12889-022-13432-1.

Age patterns of HIV incidence in eastern and southern Africa: a modelling analysis of observational population-based cohort studies

BACKGROUND

As the HIV epidemic in sub-Saharan Africa matures, evidence about the age distribution of new HIV infections and how this distribution has changed over the epidemic is needed to guide HIV prevention. We aimed to assess trends in age-specific HIV incidence in six population-based cohort studies in eastern and southern Africa, reporting changes in mean age at infection, age distribution of new infections, and birth cohort cumulative incidence.

METHODS

We used a Bayesian model to reconstruct age-specific HIV incidence from repeated observations of individuals' HIV serostatus and survival collected among population HIV cohorts in rural Malawi, South Africa, Tanzania, Uganda, and Zimbabwe, in a collaborative analysis of the ALPHA network. We modelled HIV incidence rates by age, time, and sex using smoothing splines functions. We estimated incidence trends separately by sex and study. We used estimated incidence and prevalence results for 2000-17, standardised to study population distribution, to estimate mean age at infection and proportion of new infections by age. We also estimated cumulative incidence (lifetime risk of infection) by birth cohort.

FINDINGS

Age-specific incidence declined at all ages, although the timing and pattern of decline varied by study. The mean age at infection was higher in men (cohort mean 27·8-34·6 years) than in women (24·8-29·6 years). Between 2000 and 2017, the mean age at infection per cohort increased slightly: 0·5 to 2·8 years among men and -0·2 to 2·5 years among women. Across studies, between 38% and 63% (cohort medians) of the infections in women were among those aged 15-24 years and between 30% and 63% of infections in men were in those aged 20-29 years. Lifetime risk of HIV declined for successive birth cohorts.

INTERPRETATION

HIV incidence declined in all age groups and shifted slightly to older ages. Disproportionate new HIV infections occur among women aged 15-24 years and men aged 20-29 years, supporting focused prevention in these groups. However, 40-60% of infections were outside these ages, emphasising the importance of providing appropriate HIV prevention to adults of all ages.

FUNDING

Bill & Melinda Gates Foundation.

Declining trend in HIV new infections in Guangxi, China: insights from linking reported HIV/AIDS cases with CD4-at-diagnosis data

Background

The Guangxi Zhuang Autonomous Region bears a relatively high burden of HIV/AIDS infection. The number of accumulatively reported HIV/AIDS cases in Guangxi is the third highest among 31 provinces or Autonomous Region from 2004 to 2007, changed to the second highest between 2011 and 2013, then returned to the third highest again after 2014. We aim to estimate the new infections and evaluate the real-time HIV epidemic in Guangxi, China, in order to reveal the rule of HIV transmission.

Methods

Firstly, the number of annually reported HIV and AIDS cases, as well as the number of cases linked with CD4 data are extracted from the HIV/AIDS information system in China. Secondly, two CD4-staged models are formulated by linking the with-host information on CD4 level to between-host transmission and surveillance data. Thirdly, new HIV infections, diagnosis rates and undiagnosed infections over time are estimated by using Bayesian method and Maximum Likelihood Estimation method.

Results

The data reveal that the newly reported cases have been decreasing since 2011, while lots of cases are identified at late CD4 stage. The data fitted results indicate that both models can describe the trend of the epidemic well. The estimation results show that the new and undiagnosed infections began to decrease from the period2006 - 2008. However, the diagnosis probabilities/rates keep at a very low level, and there are still a large number of infections undiagnosed, most of which have a large probability to be identified at late CD4 stage.

Conclusions

Our findings suggest that HIV/AIDS epidemic in Guangxi has been controlled to a certain extent, while the diagnosis rate still needs to be improved. More attentions should be paid to identify infections at their early CD4 stages. Meanwhile, comprehensive intervention measures should be continually strengthened in avoid of the rebound of new infections.

Modeling the effect of delay strategy on transmission dynamics of HIV/AIDS disease

In this manuscript, we investigate a nonlinear delayed model to study the dynamics of human-immunodeficiency-virus in the population. For analysis, we find the equilibria of a susceptible-infectious-immune system with a delay term. The well-established tools such as the Routh-Hurwitz criterion, Volterra-Lyapunov function, and Lasalle invariance principle are presented to investigate the stability of the model. The reproduction number and sensitivity of parameters are investigated. If the delay tactics are decreased, then the disease is endemic. On the other hand, if the delay tactics are increased then the disease is controlled in the population. The effect of the delay tactics with subpopulations is investigated. More precisely, all parameters are dependent on delay terms. In the end, to give the strength to a theoretical analysis of the model, a computer simulation is presented.