Modelling the geographical spread of HIV among MSM in Guangdong, China: a metapopulation model considering the impact of pre-exposure prophylaxis

Jing, Fengshi; Yang, Ye; Zhou, Yi; Zhou, Hanchu; Xu, Zhongzhi; Lü, Ying; Tao, Xiaoyu; Cheng, Weibin; Jing-zhen, Tian; Tang, Weiming; Wu, Dan

doi:10.1098/rsta.2021.0126

Cited by 6 publications

(8 citation statements)

References 30 publications

(44 reference statements)

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“…This finding explains why this study's monitoring/evaluation of HIV/AIDs prevention programmes suggested a high extent. The findings, however, contradict other studies that documented that the rising frequency of sexually transmitted illnesses, especially HIV/AIDS, demonstrates that previous attempts to combat the pandemic have been insufficient, even with antiretroviral therapy (Kalichman, Eaton, and Kalichman 2021;Mosha et al 2022;Jing et al 2022;Thitipatarakorn et al 2022). The disparity in results might be related to variations in the factors included in the investigations.…”

Section: Discussion Of Findingscontrasting

confidence: 84%

Care/Support, Location, and the Monitoring/Evaluation of HIV/AIDs Prevention Programs: The Case of Southern Senatorial District of Cross River State, Nigeria

Akah¹,

Ekpo²,

Owan³

2022

The International Journal of Interdisciplinary Educational Stud

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This study analysed the monitoring and evaluation of HIV/AIDS prevention programmes in the Southern Senatorial District of Cross River State, Nigeria. The study considered different levels of care/support and tested for locational variations in the monitoring/evaluation of HIV/AIDs prevention programmes. A descriptive survey design was utilised. This study covered 596 public health employees (doctors, nurses, pharmacists, and laboratory employees) in the study area. Using the proportional stratified random sampling procedure, a sample of 239 respondents was chosen. Data was collected using a questionnaire constructed by the researchers and validated by specialists. Data gathered were analysed using descriptive and inferential statistics. Results indicated that HIV/AIDs programmes had been successfully monitored/evaluated to a high extent. High success rates in the monitoring/evaluation of HIV/AIDs prevention programmes are attributable to high rates of care/support provided to people living with HIV/AIDs. There was a significant variation in the monitoring/evaluation of HIV/AIDs prevention programmes based on the location of health facilities, with higher rates recorded for urban areas. Based on the findings, it was concluded that the monitoring/evaluation of HIV/AIDs prevention programmes in the Southern Senatorial District of Cross River State had recorded a significant level of success. The study recommended, among others, that there should be even distribution of medical facilities, resources and personnel to both urban and rural areas to promote equity and access to materials needed to contain or mitigate the spread of the pandemic across all locations.

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Section: Discussion Of Findingscontrasting

confidence: 84%

Care/Support, Location, and the Monitoring/Evaluation of HIV/AIDs Prevention Programs: The Case of Southern Senatorial District of Cross River State, Nigeria

Akah¹,

Ekpo²,

Owan³

2022

The International Journal of Interdisciplinary Educational Stud

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“…Another area for future research is how to incorporate interventions into the model. This could be done by dividing the individuals with HIV into asymptomatic and symptomatic individuals and treating symptomatic individuals as in Salman 20 or dividing these individuals into more classes, including those on PrEP and antiretroviral therapy as in Jing et al, 17 in order to model these treatments. There are many other papers modeling HIV interventions, including Zhang et al, 15 Babaei et al, 13 Gountas et al, 18 Des Jarlais et al, 14 and Flountzi et al 45 and these give other options for modeling HIV interventions.…”

Section: Discussionmentioning

confidence: 99%

“…and note (17) is the rate at which infected PWIDs visit infected needles and leave the needles uninfected. This completes our interpretation of Equations ( 15) and ( 16).…”

Section: Development Of Greenhalgh and Hay's Modelmentioning

confidence: 99%

“…Among Chinese young people most cases of HIV happen in MSM. Jing et al 17 use a metapopulation approach to examine how pre‐exposure prophylaxis (PrEP) will affect the spread of a theoretical novel HIV genotype in this subpopulation in Guangdong, China. This article is relevant to forecasting the spatial HIV spread in MSM from diverse regions and looks at the role of prefecture‐level cities in containing HIV in the Guangdong region.…”

Section: Introductionmentioning

confidence: 99%

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Incorporation of awareness programs into a model of the spread of HIV/AIDS among people who inject drugs

Alsharari

Greenhalgh

2022

Engineering Reports

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Mathematical modeling techniques have been used extensively during the human immunodeficiency virus (HIV) epidemic. Drug injection causes increased HIV spread in most countries globally. The media is crucial in spreading health awareness by changing mixing behavior. The published studies show some of the ways that differential equation models can be employed to explain how media awareness programs influence the spread and containment of disease (Greenhalgh et al. Appl Math Comput. 2015;251:539-563). Here we build a differential equation model which shows how disease awareness programs can alter the HIV prevalence in a group of people who inject drugs (PWIDs). This builds on previous work by Greenhalgh and Hay (1997) and Liang et al. (2016).We have constructed a mathematical model to describe the improved model that reduces the spread of the diseases through the effect of awareness of disease on sharing needles and syringes among the PWID population. The model supposes that PWIDs clean their needles before use rather than after. We carry out a steady state analysis and examine local stability. Our discussion has been focused on two ways of studying the influence of awareness of infection levels in epidemic modeling. The key biological parameter of our model is the basic reproductive number R 0 . R 0 is a crucial number which determines the behavior of the infection. We find that if R 0 is less than one then the disease-free steady state is the unique steady state and moreover whatever the initial fraction of infected individuals then the disease will die out as time becomes large. If R 0 exceeds one there is the disease-free steady state and a unique steady state with disease present. We also showed that the disease-free steady state is locally asymptotically stable if R 0 is less than one, neutrally stable if R 0 is equal to one and unstable if R 0 exceeds one. In the last case, when R 0 is greater than one the endemic steady state was locally asymptotically stable. Our analytical results are confirmed by using simulation with realistic parameter values. In nontechnical terms, the number R 0 is a critical value describing how the disease will spread.

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“…Human mobility also plays a crucial role in the spread of HIV among at-risk populations, such as men who have sex with men (MSM). Dan Wu and colleagues characterized the behavioural dynamics underlying the spread of HIV within and between cities in Guangdong province, China, by harnessing the multi-sourced big data from MSM social networking sites, offline human mobility network, and self-reported sexual behaviours among MSM [ 4 ]. Their study demonstrated that the adoption of pre-exposure prophylaxis (PrEP) by MSM significantly delayed the occurrence of HIV in all cities.…”

mentioning

confidence: 99%

Data science approaches to infectious disease surveillance

Zhang

2021

Phil. Trans. R. Soc. A.

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Novel data science approaches are needed to confront large-scale infectious disease epidemics such as COVID-19, human immunodeficiency viruses, African swine flu and Ebola. Human beings are now equipped with richer data and more advanced data analytics methodologies, many of which have become available only in the last decade. The theme issue Data Science Approaches to Infectious Diseases Surveillance reports the latest interdisciplinary research on developing novel data science methodologies to capitalize on the rich ‘big data’ of human behaviours to confront infectious diseases, with a particular focus on combating the ongoing COVID-19 pandemic. Compared to conventional public health research, articles in this issue present innovative data science approaches that were not possible without the growing human behaviour data and the recent advances in information and communications technology. This issue has 12 research papers and one review paper from a strong lineup of contributors from multiple disciplines, including data science, computer science, computational social sciences, applied maths, statistics, physics and public health. This introductory article provides a brief overview of the issue and discusses the future of this emerging field. This article is part of the theme issue ‘Data science approaches to infectious disease surveillance’.

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Modelling the geographical spread of HIV among MSM in Guangdong, China: a metapopulation model considering the impact of pre-exposure prophylaxis

Cited by 6 publications

References 30 publications

Care/Support, Location, and the Monitoring/Evaluation of HIV/AIDs Prevention Programs: The Case of Southern Senatorial District of Cross River State, Nigeria

Care/Support, Location, and the Monitoring/Evaluation of HIV/AIDs Prevention Programs: The Case of Southern Senatorial District of Cross River State, Nigeria

Incorporation of awareness programs into a model of the spread of HIV/AIDS among people who inject drugs

Data science approaches to infectious disease surveillance

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