The impact of disruptions due to COVID‐19 on HIV transmission and control among men who have sex with men in China

INTRODUCTION: The COVID-19 pandemic is impacting HIV care globally, with gaps in HIV treatment expected to increase HIV transmission and HIV-related mortality. We estimated how COVID-19-related disruptions could impact HIV transmission and mortality among men who have sex with men (MSM) in four cities in China, over a one- and five-year time horizon. METHODS: Regional data from China indicated that the number of MSM undergoing facility-based HIV testing reduced by 59% during the COVID-19 pandemic, alongside reductions in ART initiation (34%), numbers of all sexual partners (62%) and consistency of condom use (25%), but initial data indicated no change in viral suppression. A mathematical model of HIV transmission/treatment among MSM was used to estimate the impact of disruptions on HIV infections/HIV-related deaths. Disruption scenarios were assessed for their individual and combined impact over one and five years for 3/4/6-month disruption periods, starting from 1 January 2020. RESULTS: Our model predicted new HIV infections and HIV-related deaths would be increased most by disruptions to viral suppression, with 25% reductions (25% virally suppressed MSM stop taking ART) for a three-month period increasing HIV infections by 5% to 14% over one year and deaths by 7% to 12%. Observed reductions in condom use increased HIV infections by 5% to 14% but had minimal impact (<1%) on deaths. Smaller impacts on infections and deaths (<3%) were seen for disruptions to facility HIV testing and ART initiation, but reduced partner numbers resulted in 11% to 23% fewer infections and 0.4% to 1.0% fewer deaths. Longer disruption periods (4/6 months) amplified the impact of disruption scenarios. When realistic disruptions were modelled simultaneously, an overall decrease in new HIV infections occurred over one year (3% to 17%), but not for five years (1% increase to 4% decrease), whereas deaths mostly increased over one year (1% to 2%) and five years (1.2 increase to 0.3 decrease). CONCLUSIONS: The overall impact of COVID-19 on new HIV infections and HIV-related deaths is dependent on the nature, scale and length of the various disruptions. Resources should be directed to ensuring levels of viral suppression and condom use are maintained to mitigate any adverse effects of COVID-19-related disruption on HIV transmission and control among MSM in China

Modelling the impact of an HIV testing intervention on HIV transmission among men who have sex with men in China

OBJECTIVES: An intervention developed through participatory crowdsourcing methods increased HIV self-testing among men who have sex with men [MSM; relative risk (RR) = 1.89]. We estimated the long-term impact of this intervention on HIV transmission among MSM in four cities (Guangzhou, Shenzhen, Jinan and Qingdao). METHODS: A mathematical model of HIV transmission, testing and treatment among MSM in China was parameterized using city-level demographic and sexual behaviour data and calibrated to HIV prevalence, diagnosis and antiretroviral therapy (ART) coverage data. The model was used to project the HIV infections averted over 20 years (2016-2036) from the intervention to increase self-testing, compared with current testing rates. RESULTS: Running the intervention once would avert < 2.2% infections over 20 years. Repeating the intervention (RR = 1.89) annually would avert 6.4-10.7% of new infections, while further increases in the self-testing rate (hypothetical RR = 3) would avert 11.7-20.7% of new infections. CONCLUSIONS: Repeated annual interventions would give a three- to seven-fold increase in long-term impact compared with a one-off intervention. Other interventions will be needed to more effectively reduce the HIV burden in this population

A scoping review of antibiotic use practices and drivers of inappropriate antibiotic use in animal farms in WHO Southeast Asia region

Antibiotic use (ABU) plays an important role in the proliferation of antimicrobial resistance (AMR). Global antimicrobial consumption in food production is projected to rise by 67% from 2010 to 2030, but available estimates are limited by the scarcity of ABU data and absence of global surveillance systems. The WHO South-East Asia (WHO SEA) region is at high risk of emergence of AMR, likely driven by intensifying farm operations and worsening ABU hotspots. However, little is known about farm-level ABU practices in the region. To summarize emerging evidence and research gaps, we conducted a scoping review of ABU practices following the Arksey and O'Malley methodological framework. We included studies published between 2010 and 2021 on farm-level ABU/AMR in the 11 WHO SEA member states, and databases were last searched on 31 October 2021. Our search strategy identified 184 unique articles, and 25 publications underwent full-text eligibility assessment. Seventeen studies, reported in 18 publications, were included in the scoping review. We found heterogeneity in the categorizations, definitions, and ABU characterization methods used across studies and farm types. Most studies involved poultry, pig, and cattle farms, and only one study examined aquaculture. Most studies evaluated ABU prevalence by asking respondents about the presence or absence of ABU in the farm. Only two studies quantified antibiotic consumption, and sampling bias and lack of standardized data collection methods were identified as key limitations. Emerging evidence that farm workers had difficulty differentiating antibiotics from other substances contributed to the uncertainty about the reliability of self-reported data without other validation techniques. ABU for growth promotion and treatment were prevalent. We found a large overlap in the critically important antibiotics used in farm animals and humans. The ease of access to antibiotics compounded by the difficulties in accessing quality veterinary care and preventive services likely drive inappropriate ABU in complex ways

Modelling the impact of an HIV testing intervention on HIV transmission among men who have sex with men in China

Objectives An intervention developed through participatory crowdsourcing methods increased HIV self-testing among men who have sex with men [MSM; relative risk (RR) = 1.89]. We estimated the long-term impact of this intervention on HIV transmission among MSM in four cities (Guangzhou, Shenzhen, Jinan and Qingdao). Methods A mathematical model of HIV transmission, testing and treatment among MSM in China was parameterized using city-level demographic and sexual behaviour data and calibrated to HIV prevalence, diagnosis and antiretroviral therapy (ART) coverage data. The model was used to project the HIV infections averted over 20 years (2016-2036) from the intervention to increase self-testing, compared with current testing rates. Results Running the intervention once would avert < 2.2% infections over 20 years. Repeating the intervention (RR = 1.89) annually would avert 6.4-10.7% of new infections, while further increases in the self-testing rate (hypothetical RR = 3) would avert 11.7-20.7% of new infections. Conclusions Repeated annual interventions would give a three- to seven-fold increase in long-term impact compared with a one-off intervention. Other interventions will be needed to more effectively reduce the HIV burden in this population

Comparison of empirically derived and model-based estimates of key population HIV incidence and the distribution of new infections by population group in sub-Saharan Africa

Background: The distribution of new HIV infections among key populations, including female sex workers (FSWs), gay men and other men who have sex with men (MSM), and people who inject drugs (PWID) are essential information to guide an HIV response, but data are limited in sub-Saharan Africa (SSA). We analyzed empirically derived and mathematical model-based estimates of HIV incidence among key populations and compared with the Joint United Nations Programme on HIV/AIDS (UNAIDS) estimates.Methods: We estimated HIV incidence among FSW and MSM in SSA by combining meta-analyses of empirical key population HIV incidence relative to the total population incidence with key population size estimates (KPSE) and HIV prevalence. Dynamic HIV transmission model estimates of HIV incidence and percentage of new infections among key populations were extracted from 94 country applications of 9 mathematical models. We compared these with UNAIDS-reported distribution of new infections, implied key population HIV incidence and incidence-to-prevalence ratios.Results: Across SSA, empirical FSW HIV incidence was 8.6-fold (95% confidence interval: 5.7 to 12.9) higher than total population female 15–39 year incidence, and MSM HIV incidence was 41.8-fold (95% confidence interval: 21.9 to 79.6) male 15–29 year incidence. Combined with KPSE, these implied 12% of new HIV infections in 2021 were among FSW and MSM (5% and 7% respectively). In sensitivity analysis varying KPSE proportions within 95% uncertainty range, the proportion of new infections among FSW and MSM was between 9% and 19%. Insufficient data were available to estimate PWID incidence rate ratios. Across 94 models, median proportion of new infections among FSW, MSM, and PWID was 6.4% (interquartile range 3.2%–11.7%), both much lower than the 25% reported by UNAIDS.Conclusion: Empirically derived and model-based estimates of HIV incidence confirm dramatically higher HIV risk among key populations in SSA. Estimated proportions of new infections among key populations in 2021 were sensitive to population size assumptions and were substantially lower than estimates reported by UNAIDS.</div

Measuring HIV acquisitions among partners of key populations: estimates from HIV transmission dynamic models

BACKGROUND: Key populations (KPs), including female sex workers (FSWs), gay men and other men who have sex with men (MSM), people who inject drugs (PWID), and transgender women (TGW) experience disproportionate risks of HIV acquisition. The UNAIDS Global AIDS 2022 Update reported that one-quarter of all new HIV infections occurred among their non-KP sexual partners. However, this fraction relied on heuristics regarding the ratio of new infections that KPs transmitted to their non-KP partners to the new infections acquired among KPs (herein referred to as "infection ratios"). We recalculated these ratios using dynamic transmission models.SETTING: One hundred seventy-eight settings (106 countries).METHODS: Infection ratios for FSW, MSM, PWID, TGW, and clients of FSW were estimated from 12 models for 2020.RESULTS: Median model estimates of infection ratios were 0.7 (interquartile range: 0.5-1.0; n = 172 estimates) and 1.2 (0.8-1.8; n = 127) for acquisitions from FSW clients and transmissions from FSW to all their non-KP partners, respectively, which were comparable with the previous UNAIDS assumptions (0.2-1.5 across regions). Model estimates for female partners of MSM were 0.5 (0.2-0.8; n = 20) and 0.3 (0.2-0.4; n = 10) for partners of PWID across settings in Eastern and Southern Africa, lower than the corresponding UNAIDS assumptions (0.9 and 0.8, respectively). The few available model estimates for TGW were higher [5.1 (1.2-7.0; n = 8)] than the UNAIDS assumptions (0.1-0.3). Model estimates for non-FSW partners of FSW clients in Western and Central Africa were high (1.7; 1.0-2.3; n = 29).CONCLUSIONS: Ratios of new infections among non-KP partners relative to KP were high, confirming the importance of better addressing prevention and treatment needs among KP as central to reducing overall HIV incidence.</p

Interactions between immunotoxicants and parasite stress: Implications for host health

Many organisms face a wide variety of biotic and abiotic stressors which reduce individual survival, interacting to further reduce fitness. Here we studied the effects of two such interacting stressors: immunotoxicant exposure and parasite infection. We model the dynamics of a within-host infection and the associated immune response of an individual. We consider both the indirect sub-lethal effects on immunosuppression and the direct effects on health and mortality of individuals exposed to toxicants. We demonstrate that sub-lethal exposure to toxicants can promote infection through the suppression of the immune system. This happens through the depletion of the immune response which causes rapid proliferation in parasite load. We predict that the within-host parasite density is maximised by an intermediate toxicant exposure, rather than continuing to increase with toxicant exposure. In addition, high toxicant exposure can alter cellular regulation and cause the breakdown of normal healthy tissue, from which we infer higher mortality risk of the host. We classify this breakdown into three phases of increasing toxicant stress, and demonstrate the range of conditions under which toxicant exposure causes failure at the within-host level. These phases are determined by the relationship between the immunity status, overall cellular health and the level of toxicant exposure. We discuss the implications of our model in the context of individual bee health. Our model provides an assessment of how pesticide stress and infection interact to cause the breakdown of the within-host dynamics of individual bees

Modelling the effect of COVID-19 mass vaccination on acute hospital admissions

Abstract Background Managing high levels of acute COVID-19 bed occupancy can affect the quality of care provided to both affected patients and those requiring other hospital services. Mass vaccination has offered a route to reduce societal restrictions while protecting hospitals from being overwhelmed. Yet, early in the mass vaccination effort, the possible impact on future bed pressures remained subject to considerable uncertainty. Objective The aim of this study was to model the effect of vaccination on projections of acute and intensive care bed demand within a 1 million resident healthcare system located in South West England. Methods An age-structured epidemiological model of the susceptible–exposed–infectious–recovered type was fitted to local data up to the time of the study, in early March 2021. Model parameters and vaccination scenarios were calibrated through a system-wide multidisciplinary working group, comprising public health intelligence specialists, healthcare planners, epidemiologists and academics. Scenarios assumed incremental relaxations to societal restrictions according to the envisaged UK Government timeline, with all restrictions to be removed by 21 June 2021. Results Achieving 95% vaccine uptake in adults by 31 July 2021 would not avert the third wave in autumn 2021 but would produce a median peak bed requirement ∼6% (IQR: 1–24%) of that experienced during the second wave (January 2021). A 2-month delay in vaccine rollout would lead to significantly higher peak bed occupancy, at 66% (11–146%) of that of the second wave. If only 75% uptake was achieved (the amount typically associated with vaccination campaigns), then the second wave peak for acute and intensive care beds would be exceeded by 4% and 19%, respectively, an amount which would seriously pressure hospital capacity. Conclusion Modelling influenced decision-making among senior managers in setting COVID-19 bed capacity levels, as well as highlighting the importance of public health in promoting high vaccine uptake among the population. Forecast accuracy has since been supported by actual data collected following the analysis, with observed peak bed occupancy falling comfortably within the inter-quartile range of modelled projections. </jats:sec