Modelling the impact of HIV on the populations of South Africa and Botswana

Epidemiological Characteristics and Transmissibility of Human Immunodeficiency Virus in Nanning City, China, 2001-2020

Background: Human immunodeficiency virus (HIV) is a single-stranded RNA virus that can weaken the body's cellular and humoral immunity and is a serious disease without specific drug management and vaccine. This study aimed to evaluate the epidemiologic characteristics and transmissibility of HIV.

Methods: Data on HIV follow-up were collected in Nanning City, Guangxi Zhuang Autonomous, China. An HIV transmission dynamics model was built to simulate the transmission of HIV and estimate its transmissibility by comparing the effective reproduction number (R_eff) at different stages: the rapid growth period from January 2001 to March 2005, slow growth period from April 2005 to April 2011, and the plateau from May 2011 to December 2019 of HIV in Nanning City.

Results: High-risk areas of HIV prevalence in Nanning City were mainly concentrated in suburbs. Furthermore, high-risk groups were those of older age, with lower income, and lower education levels. The R_eff in each stage (rapid growth, slow growth, and plateau) were 2.74, 1.62, and 1.15, respectively, which suggests the transmissibility of HIV in Nanning City has declined and prevention and control measures have achieved significant results.

Conclusion: Over the past 20 years, the HIV incidence in Nanning has remained at a relatively high level, but its development trend has been curbed. Transmissibility was reduced from 2.74 to 1.15. Therefore, the prevention and treatment measures in Nanning City have achieved significant improvement.

Epidemic models with discrete state structures

The state of an infectious disease can represent the degree of infectivity of infected individuals, or susceptibility of susceptible individuals, or immunity of recovered individuals, or a combination of these measures. When the disease progression is long such as for HIV, individuals often experience switches among different states. We derive an epidemic model in which infected individuals have a discrete set of states of infectivity and can switch among different states. The model also incorporates a general incidence form in which new infections are distributed among different disease states. We discuss the importance of the transmission-transfer network for infectious diseases. Under the assumption that the transmission-transfer network is strongly connected, we establish that the basic reproduction numberR 0 is a sharp threshold parameter: ifR 0 ≤ 1 , the disease-free equilibrium is globally asymptotically stable and the disease always dies out; ifR 0 > 1 , the disease-free equilibrium is unstable, the system is uniformly persistent and initial outbreaks lead to persistent disease infection. For a restricted class of incidence functions, we prove that there is a unique endemic equilibrium and it is globally asymptotically stable whenR 0 > 1 . Furthermore, we discuss the impact of different state structures onR 0 , on the distribution of the disease states at the unique endemic equilibrium, and on disease control and preventions. Implications to the COVID-19 pandemic are also discussed.

A stochastic SIR network epidemic model with preventive dropping of edges

A Markovian Susceptible [Formula: see text] Infectious [Formula: see text] Recovered (SIR) model is considered for the spread of an epidemic on a configuration model network, in which susceptible individuals may take preventive measures by dropping edges to infectious neighbours. An effective degree formulation of the model is used in conjunction with the theory of density dependent population processes to obtain a law of large numbers and a functional central limit theorem for the epidemic as the population size [Formula: see text], assuming that the degrees of individuals are bounded. A central limit theorem is conjectured for the final size of the epidemic. The results are obtained for both the Molloy-Reed (in which the degrees of individuals are deterministic) and Newman-Strogatz-Watts (in which the degrees of individuals are independent and identically distributed) versions of the configuration model. The two versions yield the same limiting deterministic model but the asymptotic variances in the central limit theorems are greater in the Newman-Strogatz-Watts version. The basic reproduction number [Formula: see text] and the process of susceptible individuals in the limiting deterministic model, for the model with dropping of edges, are the same as for a corresponding SIR model without dropping of edges but an increased recovery rate, though, when [Formula: see text], the probability of a major outbreak is greater in the model with dropping of edges. The results are specialised to the model without dropping of edges to yield conjectured central limit theorems for the final size of Markovian SIR epidemics on configuration-model networks, and for the size of the giant components of those networks. The theory is illustrated by numerical studies, which demonstrate that the asymptotic approximations are good, even for moderate N.

Policy-maker attitudes to the ageing of the HIV cohort in Botswana

Background: The roll out of antiretroviral therapy in Botswana, as in many countries with near universal access to treatment, has transformed HIV into a complex yet manageable chronic condition and has led to the emergence of a population aging with HIV. Although there has been some realization of this development at international level, no clear defined intervention strategy has been established in many highly affected countries. Therefore we explored attitudes of policy-makers and service providers towards HIV among older adults (50 years or older) in Botswana. Methods: We conducted qualitative face-to-face interviews with 15 consenting personnel from the Ministry of Health, medical practitioners and non-governmental organizations involved in the administration of medical services, planning, strategies and policies that govern social, physical and medical intervention aimed at people living with HIV and health in general. The Shiffman and Smith Framework of how health issues become a priority was used as a guide for our analysis. Results: Amidst an HIV prevalence of 25% among those aged 50–64 years, the respondents passively recognized the predicament posed by a population aging with HIV but exhibited a lack of comprehension and acknowledgement of the extent of the issue. An underlying persistent ageist stigma regarding sexual behaviour existed among a number of interviewees. Respondents also noted the lack of defined geriatric care within the provision of the national health care system. There seemed, however, to be a debate among the policy strategists and care providers as to whether the appropriate response should be specifically towards older adults living with HIV or rather to improve health services for older adults more generally. Respondents acknowledged that health systems in Botswana are still configured for individual diseases rather than coexisting chronic diseases even though it has become increasingly common for patients, particularly the aged, to have two or more medical conditions at the same time. Conclusions: HIV among older adults remains a low priority among policy-makers in Botswana but is at least now on the agenda. Action will require more concerted efforts to recognize HIV as a lifelong infection and putting greater emphasis on targeted care for older adults, focussing on multimorbidity.

Behavioural change models for infectious disease transmission: a systematic review (2010-2015)

We review behavioural change models (BCMs) for infectious disease transmission in humans. Following the Cochrane collaboration guidelines and the PRISMA statement, our systematic search and selection yielded 178 papers covering the period 2010-2015. We observe an increasing trend in published BCMs, frequently coupled to (re)emergence events, and propose a categorization by distinguishing how information translates into preventive actions. Behaviour is usually captured by introducing information as a dynamic parameter (76/178) or by introducing an economic objective function, either with (26/178) or without (37/178) imitation. Approaches using information thresholds (29/178) and exogenous behaviour formation (16/178) are also popular. We further classify according to disease, prevention measure, transmission model (with 81/178 population, 6/178 metapopulation and 91/178 individual-level models) and the way prevention impacts transmission. We highlight the minority (15%) of studies that use any real-life data for parametrization or validation and note that BCMs increasingly use social media data and generally incorporate multiple sources of information (16/178), multiple types of information (17/178) or both (9/178). We conclude that individual-level models are increasingly used and useful to model behaviour changes. Despite recent advancements, we remain concerned that most models are purely theoretical and lack representative data and a validation process.