Detailed Transmission Network Analysis of a Large Opiate-Driven Outbreak of HIV Infection in the United States

Potential impact of curative and preventive interventions toward hepatitis C elimination in people who inject drugs-A network modeling study

BACKGROUND

Injection-equipment-sharing networks play an important role in hepatitis C virus (HCV) transmission among people who inject drugs (PWID). Direct-acting antiviral (DAA) treatments for HCV infection and interventions to prevent HCV transmission are critical components of an overall hepatitis C elimination strategy, but how they contribute to the elimination outcomes in different PWID network settings are unclear.

METHODS

We developed an agent-based network model of HCV transmission through the sharing of injection equipment among PWID and parameterized and calibrated the model with rural PWID data in the United States. We modeled curative and preventive interventions at annual coverage levels of 12.5 %, 25 %, or 37.5 % (cumulative percentage of eligible individuals engaged), and two allocation approaches: random vs targeting PWID with more injection partners (hereafter 'degree-based'). We compared the impact of these intervention strategies on prevalence and incidence of HCV infections. We conducted sensitivity analysis on key parameters governing the effects of curative and preventive interventions and PWID network characteristics.

RESULTS

Combining curative and preventive interventions at 37.5 % annual coverage with degree-based allocation decreased prevalence and incidence of HCV infection by 67 % and 70 % over two years, respectively. Curative interventions decreased prevalence by six to 12 times more than preventive interventions, while curative and preventive interventions had comparable effectiveness on reducing incidence. Intervention impact increased with coverage almost linearly across all intervention strategies, and degree-based allocation was always more effective than random allocation, especially for preventive interventions. Results were sensitive to parameter values defining intervention effects and network mean degree.

CONCLUSION

DAA treatments are effective in reducing both prevalence and incidence of HCV infection in PWID, but preventive interventions play a significant role in reducing incidence when intervention coverage is low. Increasing coverage, including efforts in reaching individuals with the most injection partners, preventing reinfection, and improving compliance and retention in preventive services can substantially improve the outcomes. PWID network characteristics should be considered when designing hepatitis C elimination programs.

AUTO-TUNE: selecting the distance threshold for inferring HIV transmission clusters

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained heterosexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

Physician Reluctance to Intervene in Addiction: A Systematic Review

Importance

The overdose epidemic continues in the US, with 107 941 overdose deaths in 2022 and countless lives affected by the addiction crisis. Although widespread efforts to train and support physicians to implement medications and other evidence-based substance use disorder interventions have been ongoing, adoption of these evidence-based practices (EBPs) by physicians remains low.

Objective

To describe physician-reported reasons for reluctance to address substance use and addiction in their clinical practices using screening, treatment, harm reduction, or recovery support interventions.

Data Sources

A literature search of PubMed, Embase, Scopus, medRxiv, and SSRN Medical Research Network was conducted and returned articles published from January 1, 1960, through October 5, 2021.

Study Selection

Publications that included physicians, discussed substance use interventions, and presented data on reasons for reluctance to intervene in addiction were included.

Data Extraction and Synthesis

Two reviewers (L.N., M.C., L.F., J.P., C.S., and S.W.) independently reviewed each publication; a third reviewer resolved discordant votes (M.C. and W.C.). This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines and the theoretical domains framework was used to systematically extract reluctance reasons.

Main Outcomes and Measures

The primary outcome was reasons for physician reluctance to address substance use disorder. The association of reasons for reluctance with practice setting and drug type was also measured. Reasons and other variables were determined according to predefined criteria.

Results

A total of 183 of 9308 returned studies reporting data collected from 66 732 physicians were included. Most studies reported survey data. Alcohol, nicotine, and opioids were the most often studied substances; screening and treatment were the most often studied interventions. The most common reluctance reasons were lack of institutional support (173 of 213 articles [81.2%]), knowledge (174 of 242 articles [71.9%]), skill (170 of 230 articles [73.9%]), and cognitive capacity (136 of 185 articles [73.5%]). Reimbursement concerns were also noted. Bivariate analysis revealed associations between these reasons and physician specialty, intervention type, and drug.

Conclusions and Relevance

In this systematic review of reasons for physician reluctance to intervene in addiction, the most common reasons were lack of institutional support, knowledge, skill, and cognitive capacity. Targeting these reasons with education and training, policy development, and program implementation may improve adoption by physicians of EBPs for substance use and addiction care. Future studies of physician-reported reasons for reluctance to adopt EBPs may be improved through use of a theoretical framework and improved adherence to and reporting of survey development best practices; development of a validated survey instrument may further improve study results.

Characterising HIV-1 transmission in Victoria, Australia: a molecular epidemiological study

Background

In Australia the incidence of HIV has declined steadily, yet sustained reduction of HIV transmission in this setting requires improved public health responses. As enhanced public health responses and prioritisation of resources may be guided by molecular epidemiological data, here we aimed to assess the applicability of these approaches in Victoria, Australia.

Methods

A comprehensive collection of HIV-1 pol sequences from individuals diagnosed with HIV in Victoria, Australia, between January 1st 2000 and December 31st 2020 were deidentified and used as the basis of our assessment. These sequences were subtyped and surveillance drug resistance mutations (SDRMs) identified, before definition of transmission groups was performed using HIV-TRACE (0.4.4). Phylodynamic methods were applied using BEAST (2.6.6), assessing effective reproductive numbers for large groups, and additional demographic data were integrated to provide a high resolution view of HIV transmission in Victoria on a decadal time scale.

Findings

Based on standard settings for HIV-TRACE, 70% (2438/3507) of analysed HIV-1 pol sequences were readily assigned to a transmission group. Individuals in transmission groups were more commonly males (aOR 1.50), those born in Australia (aOR 2.13), those with probable place of acquisition as Victoria (aOR 6.73), and/or those reporting injectable drug use (aOR 2.13). SDRMs were identified in 375 patients (10.7%), with sustained transmission of these limited to a subset of smaller groups. Informative patterns of epidemic growth, stabilisation, and decline were observed; many transmission groups showed effective reproductive numbers (R e ) values reaching greater than 4.0, representing considerable epidemic growth, while others maintained low R e values.

Interpretation

This study provides a high resolution view of HIV transmission in Victoria, Australia, and highlights the potential of molecular epidemiology to guide and enhance public health responses in this setting. This informs ongoing discussions with community groups on the acceptability and place of molecular epidemiological approaches in Australia.

Funding

National Health and Medical Research Council, Australian Research Council.

Homophily and social mixing in a small community: Implications for infectious disease transmission

Community mixing patterns by sociodemographic traits can inform the risk of epidemic spread among groups, and the balance of in- and out-group mixing affects epidemic potential. Understanding mixing patterns can provide insight about potential transmission pathways throughout a community. We used a snowball sampling design to enroll people recently diagnosed with SARS-CoV-2 in an ethnically and racially diverse county and asked them to describe their close contacts and recruit some contacts to enroll in the study. We constructed egocentric networks of the participants and their contacts and assessed age-mixing, ethnic/racial homophily, and gender homophily. The total size of the egocentric networks was 2,544 people (n = 384 index cases + n = 2,160 recruited peers or other contacts). We observed high rates of in-group mixing among ethnic/racial groups compared to the ethnic/racial proportions of the background population. Black or African-American respondents interacted with a wider range of ages than other ethnic/racial groups, largely due to familial relationships. The egocentric networks of non-binary contacts had little age diversity. Black or African-American respondents in particular reported mixing with older or younger family members, which could increase the risk of transmission to vulnerable age groups. Understanding community mixing patterns can inform infectious disease risk, support analyses to predict epidemic size, or be used to design campaigns such as vaccination strategies so that community members who have vulnerable contacts are prioritized.

Using the Molecular Transmission Networks to Analyze the Epidemic Characteristics of HIV-1 CRF08_BC in Kunming, Yunnan

HIV-1CRF08_BC is the most prevalent epidemic subtype among heterosexual (HET) and intravenous drug users (IDUs) in Kunming, Yunnan. Using the pol region of gene sequences derived from molecular epidemiological surveys, we developed a molecular transmission network for the purpose of analyzing its epidemiological characteristics, assessing its epidemiological trends, identifying its potential transmission relationships, and developing targeted interventions. HyPhy 2.2.4 was used to calculate pairwise genetic distances between sequences; GraphPad-Prism 8.0 was employed to determine the standard genetic distance; and Cytoscope 3.7.2 was applied to visualize the network. We used the network analysis tools to investigate network characteristics and the Molecular Complex Detection (MCODE) tool to observe the growth of the network. We utilized a logistic regression model to examine the factors influencing clustering and a zero-inflated Poisson model to investigate the factors influencing potential transmission links. At the standard genetic distance threshold of 0.008, 406 out of 858 study participants were clustered in 132 dissemination networks with a total network linkage of 868, and the number of links per sequence ranged from 1 to 19. The MCODE analysis identified three significant modular clusters in the networks, with network scores ranging from 4.9 to 7. In models of logistic regression, HET, middle-aged and elderly individuals, and residents of northern and southeastern Kunming were more likely to enter the transmission network. According to the zero-inflated Poisson model, age, transmission category, sampling year, marital status, and CD4+ T level had a significant effect on the size of links. The molecular clusters in Kunming's molecular transmission network are specific and aggregate to a certain extent. HIV-1 molecular network analysis provided information on local transmission characteristics, and these findings helped to determine the priority of transmission-reduction interventions.

AUTO-TUNE: SELECTING THE DISTANCE THRESHOLD FOR INFERRING HIV TRANSMISSION CLUSTERS

Molecular surveillance of viral pathogens and inference of transmission networks from genomic data play an increasingly important role in public health efforts, especially for HIV-1. For many methods, the genetic distance threshold used to connect sequences in the transmission network is a key parameter informing the properties of inferred networks. Using a distance threshold that is too high can result in a network with many spurious links, making it difficult to interpret. Conversely, a distance threshold that is too low can result in a network with too few links, which may not capture key insights into clusters of public health concern. Published research using the HIV-TRACE software package frequently uses the default threshold of 0.015 substitutions/site for HIV pol gene sequences, but in many cases, investigators heuristically select other threshold parameters to better capture the underlying dynamics of the epidemic they are studying. Here, we present a general heuristic scoring approach for tuning a distance threshold adaptively, which seeks to prevent the formation of giant clusters. We prioritize the ratio of the sizes of the largest and the second largest cluster, maximizing the number of clusters present in the network. We apply our scoring heuristic to outbreaks with different characteristics, such as regional or temporal variability, and demonstrate the utility of using the scoring mechanism's suggested distance threshold to identify clusters exhibiting risk factors that would have otherwise been more difficult to identify. For example, while we found that a 0.015 substitutions/site distance threshold is typical for US-like epidemics, recent outbreaks like the CRF07_BC subtype among men who have sex with men (MSM) in China have been found to have a lower optimal threshold of 0.005 to better capture the transition from injected drug use (IDU) to MSM as the primary risk factor. Alternatively, in communities surrounding Lake Victoria in Uganda, where there has been sustained hetero-sexual transmission for many years, we found that a larger distance threshold is necessary to capture a more risk factor-diverse population with sparse sampling over a longer period of time. Such identification may allow for more informed intervention action by respective public health officials.

High HIV diversity, recombination, and superinfection revealed in a large outbreak among persons who inject drugs in Kentucky and Ohio, USA

We investigated transmission dynamics of a large human immunodeficiency virus (HIV) outbreak among persons who inject drugs (PWID) in KY and OH during 2017-20 by using detailed phylogenetic, network, recombination, and cluster dating analyses. Using polymerase (pol) sequences from 193 people associated with the investigation, we document high HIV-1 diversity, including Subtype B (44.6 per cent); numerous circulating recombinant forms (CRFs) including CRF02_AG (2.5 per cent) and CRF02_AG-like (21.8 per cent); and many unique recombinant forms composed of CRFs with major subtypes and sub-subtypes [CRF02_AG/B (24.3 per cent), B/CRF02_AG/B (0.5 per cent), and A6/D/B (6.4 per cent)]. Cluster analysis of sequences using a 1.5 per cent genetic distance identified thirteen clusters, including a seventy-five-member cluster composed of CRF02_AG-like and CRF02_AG/B, an eighteen-member CRF02_AG/B cluster, Subtype B clusters of sizes ranging from two to twenty-three, and a nine-member A6/D and A6/D/B cluster. Recombination and phylogenetic analyses identified CRF02_AG/B variants with ten unique breakpoints likely originating from Subtype B and CRF02_AG-like viruses in the largest clusters. The addition of contact tracing results from OH to the genetic networks identified linkage between persons with Subtype B, CRF02_AG, and CRF02_AG/B sequences in the clusters supporting de novo recombinant generation. Superinfection prevalence was 13.3 per cent (8/60) in persons with multiple specimens and included infection with B and CRF02_AG; B and CRF02_AG/B; or B and A6/D/B. In addition to the presence of multiple, distinct molecular clusters associated with this outbreak, cluster dating inferred transmission associated with the largest molecular cluster occurred as early as 2006, with high transmission rates during 2017-8 in certain other molecular clusters. This outbreak among PWID in KY and OH was likely driven by rapid transmission of multiple HIV-1 variants including de novo viral recombinants from circulating viruses within the community. Our findings documenting the high HIV-1 transmission rate and clustering through partner services and molecular clusters emphasize the importance of leveraging multiple different data sources and analyses, including those from disease intervention specialist investigations, to better understand outbreak dynamics and interrupt HIV spread.

Distinct Rates and Transmission Patterns of Major HIV-1 Subtypes among Men who Have Sex with Men in Guangxi, China

The diversity and transmission patterns of major HIV-1 subtypes among MSM population in Guangxi remains unknown. Understanding the characteristics is crucial for effective intervention strategies. Between 2016 and 2021, we recruited individuals newly diagnosed with HIV-1 from MSM population in Guangxi. HIV-1 pol region was amplified and sequenced, and constructed molecular network, assessed clustering rate, cluster growth rate, spatial clustering, and calculating the basic reproductive number (R0) based on sequences data. We identified 16 prevalent HIV-1 subtypes among Guangxi MSM, with CRF07_BC (53.1%), CRF01_AE (26.23%), and CRF55_01B (12.96%) predominating. In the network, 618 individuals (66.17%) formed 59 clusters. Factors contributing to clustering included age < 30 years (AOR = 1.35), unmarried status (AOR = 1.67), CRF07_BC subtype (AOR = 3.21), and high viral load (AOR = 1.43). CRF07_BC had a higher likelihood of forming larger clusters and having higher degree than CRF01_AE and CRF55_01B. Notably, CRF07_BC has higher cluster growth rate and higher basic reproductive number than CRF01_AE and CRF55_01B. Our findings underscore CRF07_BC as a prominent driver of HIV-1 spread among Guangxi's MSM population, highlighting the viability of targeted interventions directed at specific subtypes and super clusters to control HIV-1 transmission within this population.

HIV and HCV testing at clinical encounters among people who inject drugs, 2013-2018-Opportunities for increased testing and prevention

People who inject drugs (PWID) with unsafe injection practices have substantial risk for HIV and hepatitis C virus (HCV) infections. We describe frequency of, and factors associated with, HIV and HCV testing during clinical encounters with PWID. Inpatient and Emergency Department clinical encounters at an Atlanta hospital were abstracted from medical records spanning January 2013-December 2018. We estimated frequency of HIV and HCV testing during injection drug use (IDU)-related encounters among PWID without previous diagnoses. We assessed associations between patient factors and testing using generalized estimating equations models. HIV testing occurred in 39.3% and HCV testing occurred in 17.1% of eligible IDU-related encounters. Testing was more likely in IDU-related encounters during 2017-2018 than in encounters during 2013-2014; (HIV, AOR = 2.14, 95% CI, 1.32-3.49, p < .01). Testing was less likely among Black/African American patients compared to White patients (adjusted odds ratio [AOR]: HIV, AOR = 0.48, 95% confidence interval [CI], 0.33-0.72, p < .01); HCV, AOR = 0.41, 95% CI, 0.24-0.70, p < .01). This difference may be attributable to recent testing among Black patients in non-IDU related encounters. HIV and HCV testing improved over time; however, missed opportunities for testing still existed. Strategies should aim to improve equitable HIV and HCV testing among PWID.

Integrated Care Models: HIV and Substance Use

PURPOSE OF REVIEW

Behaviors and practices associated with substance use contribute to lack of HIV virologic suppression and onward transmission. In the USA, many recent HIV outbreaks have been connected with substance use. Evidence-based strategies for integrating care of those at risk for and living with HIV and who use substances continue to evolve. This review, based on scientific and medical literature through March 2023, provides an overview and evaluation of initiatives for integrated care aimed to serve patients at risk for and with HIV and a substance use disorder.

RECENT FINDINGS

Integrated care services can improve health outcomes for patients at risk for and with HIV and a substance use disorder; for instance, treatment for an opioid use disorder can help improve HIV viral suppression. Brick-and-mortar facilities can provide successful care integration with appropriate clinic leadership to support multidisciplinary care teams, up-to-date provider training, and sufficient pharmacy stock for substance use treatment. Delivering healthcare services to communities (e.g., mobile healthcare clinics and pharmacies, telehealth) may prove to be an effective way to provide integrated services for those with or at risk of HIV and substance use disorders. Incorporating technology (e.g., mobile phone applications) may facilitate integrated care. Other venues, including harm reduction programs and carceral settings, should be targets for integrated services. Venues providing healthcare should invest in integrated care and support legislation that increases access to services related to HIV and substance use.

Network typologies predict future molecular linkages in the network of HIV transmission

OBJECTIVE

HIV molecular transmission network typologies have previously demonstrated associations to transmission risk; however, few studies have evaluated their predictive potential in anticipating future transmission events. To assess this, we tested multiple models on statewide surveillance data from the Florida Department of Health.

DESIGN

This was a retrospective, observational cohort study examining the incidence of new HIV molecular linkages within the existing molecular network of persons with HIV (PWH) in Florida.

METHODS

HIV-1 molecular transmission clusters were reconstructed for PWH diagnosed in Florida from 2006 to 2017 using the HIV-TRAnsmission Cluster Engine (HIV-TRACE). A suite of machine-learning models designed to predict linkage to a new diagnosis were internally and temporally externally validated using a variety of demographic, clinical, and network-derived parameters.

RESULTS

Of the 9897 individuals who received a genotype within 12 months of diagnosis during 2012-2017, 2611 (26.4%) were molecularly linked to another case within 1 year at 1.5% genetic distance. The best performing model, trained on two years of data, was high performing (area under the receiving operating curve = 0.96, sensitivity = 0.91, and specificity = 0.90) and included the following variables: age group, exposure group, node degree, betweenness, transitivity, and neighborhood.

CONCLUSIONS

In the molecular network of HIV transmission in Florida, individuals' network position and connectivity predicted future molecular linkages. Machine-learned models using network typologies performed superior to models using individual data alone. These models can be used to more precisely identify subpopulations for intervention.

Social Mixing and Network Characteristics of COVID-19 Patients Before and After Widespread Interventions: A Population-based Study

SARS-CoV-2 rapidly spreads among humans via social networks, with social mixing and network characteristics potentially facilitating transmission. However, limited data on topological structural features has hindered in-depth studies. Existing research is based on snapshot analyses, preventing temporal investigations of network changes. Comparing network characteristics over time offers additional insights into transmission dynamics. We examined confirmed COVID-19 patients from an eastern Chinese province, analyzing social mixing and network characteristics using transmission network topology before and after widespread interventions. Between the two time periods, the percentage of singleton networks increased from 38.9 to 62.8 ; the average shortest path length decreased from 1.53 to 1.14 ; the average betweenness reduced from 0.65 to 0.11 ; the average cluster size dropped from 4.05 to 2.72 ; and the out-degree had a slight but nonsignificant decline from 0.75 to 0.63 Results show that nonpharmaceutical interventions effectively disrupted transmission networks, preventing further disease spread. Additionally, we found that the networks’ dynamic structure provided more information than solely examining infection curves after applying descriptive and agent-based modeling approaches. In summary, we investigated social mixing and network characteristics of COVID-19 patients during different pandemic stages, revealing transmission network heterogeneities.

Predictors of HIV Molecular Cluster Membership and Implications for Partner Services

Public health surveillance data used in HIV molecular cluster analyses lack contextual information that is available from partner services (PS) data. Integrating these data sources in retrospective analyses can enrich understanding of the risk profile of people in clusters. In this study, HIV molecular clusters were identified and matched to information on partners and other information gleaned at the time of diagnosis, including coinfection with syphilis. We aimed to produce a more complete understanding of molecular cluster membership in Houston, Texas, a city ranking ninth nationally in rate of new HIV diagnoses that may benefit from retrospective matched analyses between molecular and PS data to inform future intervention. Data from PS were matched to molecular HIV records of people newly diagnosed from 2012 to 2018. By conducting analyses in HIV-TRACE (TRAnsmission Cluster Engine) using viral genetic sequences, molecular clusters were detected. Multivariable logistic regression models were used to estimate the association between molecular cluster membership and completion of a PS interview, number of named partners, and syphilis coinfection. Using data from 4,035 people who had a viral genetic sequence and matched PS records, molecular cluster membership was not significantly associated with completion of a PS interview. Among those with sequences who completed a PS interview (n = 3,869), 45.3% (n = 1,753) clustered. Molecular cluster membership was significantly associated with naming 1 or 3+ partners compared with not naming any partners [adjusted odds ratio, aOR: 1.27 (95% confidence interval, CI: 1.08-1.50), p = .003 and aOR: 1.38 (95% CI: 1.06-1.81), p = .02]. Alone, coinfection with syphilis was not significantly associated with molecular cluster membership. Syphilis coinfection was associated with molecular cluster membership when coupled with incarceration [aOR: 1.91 (95% CI: 1.08-3.38), p = .03], a risk for treatment interruption. Enhanced intervention among those with similar profiles, such as people coinfected with other risks, may be warranted.

Missed opportunities for prevention: prevalence and incidence of human immunodeficiency virus and hepatitis C virus diagnoses among a cohort of individuals discharged from an urban hospital with injection drug-related diagnoses, 2012-2019

PURPOSE

Risk for human immunodeficiency virus (HIV) and hepatitis C virus (HCV) infections has increased due to the ongoing opioid epidemic and unsafe injection practices. We estimated the prevalence and incidence of HIV and HCV diagnoses among people who inject drugs from hospital-based clinical encounters.

METHODS

We linked clinical encounters at an Atlanta hospital during 2012-2018 with state HIV and HCV surveillance records to examine the prevalence of infections at discharge and incidence of infections post clinical encounter.

RESULTS

At discharge, 32.9% and 28.6% of patients with injection drug use-related clinical encounters had an HIV or HCV diagnosis, respectively. HIV and HCV diagnoses at the time of discharge were mostly among 40-64 years old patients, males, and Black/African Americans. Post clinical encounter, 3.8% of patients were later diagnosed with HIV, and 16.5% were later diagnosed with HCV, translating to incidence rates of 9.3 per 1000 person-years and 41.5 per 1000 person-years, respectively. The majority of HIV and HCV diagnoses post clinical encounter occurred among Black/African Americans and males. Of patients with HIV and HCV diagnoses post clinical encounter, 27.3% and 11.9% had been tested during their clinical encounter, respectively.

CONCLUSIONS

Targeted interventions for HIV/HCV prevention, screening, diagnosis, and linkage to treatment are needed to reduce the incidence of new infections among people who inject drugs.

Short-term associations of PM2.5 and PM2.5 constituents with immune biomarkers: A panel study in people living with HIV/AIDS

Studies on associations of fine particulate matter (PM_2.5) with immunity in people living with HIV/AIDS (PLWHA) were absent. We aimed to explore whether changes of immune biomarkers were associated with short-term exposure to PM_2.5 in PLWHA. Based on a panel study in Wuhan, we selected 163 PLWHA as participants with up to 4 repeated visits from March 2020 to January 2021. Immune biomarkers, including CD4⁺T cell count, CD8⁺T cell count, HIV viral load (VL) and CD4⁺T/CD8⁺T ratio were tested for all participants at each visit. Residential exposures of PM_2.5 and PM_2.5 constituents for each participant were assessed using spatial-temporal models. Linear mixed-effect models and general linear mixed models were applied to evaluate the associations between PM_2.5 and immune biomarkers. To estimate the combined effect of PM_2.5 constituents, weighted quantile sum regression and Bayesian kernel machine regression were employed. Each 10 μg/m³ increase of 7-day average PM_2.5 concentrations was associated with an 8.75 cells/mm³ (95%CI: -15.55, -1.98) decrease in CD4⁺T cell count and a 92% (OR: 1.92, 95%CI: 1.43, 2.58) increased odds ratio of detectable HIV VL. However, the odds ratio of inverted CD4⁺T/CD8⁺T was only positively associated with PM_2.5 concentrations at lag2 day (OR:1.27, 95%CI:1.02, 1.57). CD4⁺T may be a potential mediator between PM_2.5 and detectable HIV VL with 3.83% mediated proportion. Besides, the combined effect of PM_2.5 chemical constituents indicated that NO₃^- and SO₄^2- were the main constituents in reducing CD4⁺T cell count and increasing odds ratio of detectable HIV VL. Our finding revealed that short-term exposure to PM_2.5 was negatively associated with CD4⁺T cell count but positively related to the odds ratio of detectable HIV VL in PLWHA. This research may provide new evidence in associations between PM_2.5 and immune biomarkers as well as improving prognosis of PLWHA.

Brief Report: Use of Pre-Exposure Prophylaxis to Prevent Rapid HIV Transmission Among People Who Inject Drugs in Rural Counties in the United States: A Modeling Study

BACKGROUND

Despite recent HIV outbreaks among people who inject drugs (PWID) in nonurban US settings, syringe service programs (SSP) are often inaccessible in these communities. Furthermore, pre-exposure prophylaxis (PrEP) awareness and coverage for PWID is limited. We aimed to model the impact of PrEP on HIV transmission among PWID in a rural setting.

SETTING

Using a calibrated agent-based model, we simulated HIV transmission in an adult population (n = 14,573 agents) in Scott County, Indiana between 2015 and 2024.

METHODS

We modeled PrEP eligibility according to CDC guidelines for PWID. PrEP coverage increased by 15% points in the range 10%-70%. Two counterfactual scenarios were modeled: Unrestricted access for PWID and PrEP for SSP attendees . We calculated the number of new HIV infections and number of person-years on PrEP per averted infection.

RESULTS

In the status quo scenario, 153 (95% Simulation Interval: 85, 259) new HIV infections occurred among PWID over 10 years. Compared with the status quo, 40% PrEP coverage resulted in 25% fewer HIV infections in the Unrestricted access for PWID scenario and 10% fewer HIV infections in the PrEP for SSP attendees scenario. The PYPAI was 21 and 43 in the Unrestricted access for PWID and PrEP for SSP attendees scenarios, respectively.

CONCLUSION

Our modeling suggests that PrEP provides substantial benefit to PWID in rural US communities, with fewer restrictions on access providing the greatest effect. Control of HIV outbreaks will require expansion of public health interventions that meet the needs of all individuals.

A hybrid of long short-term memory neural network and autoregressive integrated moving average model in forecasting HIV incidence and morality of post-neonatal population in East Asia: global burden of diseases 2000-2019

Background

To forecast the human immunodeficiency virus (HIV) incidence and mortality of post-neonatal population in East Asia including North Korea, South Korea, Mongolia, Japan and China Mainland and Taiwan province.

Methods

The data on the incidence and mortality of HIV in post-neonatal population from East Asia were obtained from the Global Burden of Diseases (GBD). The morbidity and mortality of post-neonatal HIV population from GBD 2000 to GBD 2013 were applied as the training set and the morbidity and mortality from GBD 2014 to GBD 2019 were used as the testing set. The hybrid of ARIMA and LSTM model was used to construct the model for assessing the morbidity and mortality in the countries and territories of East Asia, and predicting the morbidity and mortality in the next 5 years.

Results

In North Korea, the incidence and mortality of HIV showed a rapid increase during 2000–2010 and a gradual decrease during 2010–2019. The incidence of HIV was predicted to be increased and the mortality was decreased. In South Korea, the incidence was increased during 2000–2010 and decreased during 2010–2019, while the mortality showed fluctuant trend. As predicted, the incidence of HIV in South Korea might be increased and the mortality might be decreased during 2020–2025. In Mongolia, the incidence and mortality were slowly decreased during 2000–2005, increased during 2005–2015, and rapidly decreased till 2019. The predicted incidence and mortality of HIV showed a decreased trend. As for Japan, the incidence of HIV was rapidly increased till 2010 and then decreased till 2015. The predicted incidence of HIV in Japan was gradually increased. The mortality of HIV in Japan was fluctuant during 2000–2019 and was slowly decreased as predicted. The incidence and mortality of HIV in Taiwan during 2000–2019 was increased on the whole. The predicted incidence of HIV during was stationary and the mortality was decreased. In terms of China Mainland, the incidence and mortality of HIV was fluctuant during 2000–2019. The predicted incidence of HIV in China Mainland was stationary while the mortality was rapidly decreased.

Conclusion

On the whole, the incidence of HIV combined with other diseases in post-neonatal population was increased before 2010 and then decreased during 2010–2019 while the mortality of those patients was decreased in East Asia.

SOPHIE: Viral outbreak investigation and transmission history reconstruction in a joint phylogenetic and network theory framework

Genomic epidemiology is now widely used for viral outbreak investigations. Still, this methodology faces many challenges. First, few methods account for intra-host viral diversity. Second, maximum parsimony principle continues to be employed for phylogenetic inference of transmission histories, even though maximum likelihood or Bayesian models are usually more consistent. Third, many methods utilize case-specific data, such as sampling times or infection exposure intervals. This impedes study of persistent infections in vulnerable groups, where such information has a limited use. Finally, most methods implicitly assume that transmission events are independent, although common source outbreaks violate this assumption. We propose a maximum likelihood framework, SOPHIE, based on the integration of phylogenetic and random graph models. It infers transmission networks from viral phylogenies and expected properties of inter-host social networks modeled as random graphs with given expected degree distributions. SOPHIE is scalable, accounts for intra-host diversity, and accurately infers transmissions without case-specific epidemiological data.

The International Virus Bioinformatics Meeting 2022

The International Virus Bioinformatics Meeting 2022 took place online, on 23-25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus-host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting.

Community and Provider Perspectives on Molecular HIV Surveillance and Cluster Detection and Response for HIV Prevention: Qualitative Findings From King County, Washington

ABSTRACT

Responding quickly to HIV outbreaks is one of four pillars of the U.S. Ending the HIV Epidemic (EHE) initiative. Inclusion of cluster detection and response in the fourth pillar of EHE has led to public discussion concerning bioethical implications of cluster detection and response and molecular HIV surveillance (MHS) among public health authorities, researchers, and community members. This study reports on findings from a qualitative analysis of interviews with community members and providers regarding their knowledge and perspectives of MHS. We identified five key themes: (a) context matters, (b) making sense of MHS, (c) messaging, equity, and resource prioritization, (d) operationalizing confidentiality, and (e) stigma, vulnerability, and power. Inclusion of community perspectives in generating innovative approaches that address bioethical concerns related to the use of MHS data is integral to ensure that widely accessible information about the use of these data is available to a diversity of community members and providers.

The impact of syringe services program closure on the risk of rebound HIV outbreaks among people who inject drugs: a modeling study

OBJECTIVE

Despite their effectiveness in preventing the transmission of HIV among people who inject drugs (PWID), syringe services programs (SSPs) in many settings are hampered by social and political opposition. We aimed to estimate the impact of closure and temporary interruption of SSP on the HIV epidemic in a rural United States setting.

METHODS

Using an agent-based model (ABM) calibrated to observed surveillance data, we simulated HIV risk behaviors and transmission in adult populations who inject and do not inject drugs in Scott County, Indiana. We projected HIV incidence and prevalence between 2020 and 2025 for scenarios with permanent closure, delayed closure (one additional renewal for 24 months before closure), and temporary closure (lasting 12 months) of an SSP in comparison to persistent SSP operation.

RESULTS

With sustained SSP operation, we projected an incidence rate of 0.15 per 100 person-years among the overall population (95% simulation interval: 0.06-0.28). Permanently closing the SSP would cause an average of 58.4% increase in the overall incidence rate during 2021-2025, resulting in a higher prevalence of 60.8% (50.9-70.6%) (18.7% increase) among PWID by 2025. A delayed closure would increase the incidence rate by 38.9%. A temporary closure would cause 12 (35.3%) more infections during 2020-2021.

CONCLUSION

Our analysis suggests that temporary interruption and permanent closure of existing SSPs operating in rural United States may lead to 'rebound' HIV outbreaks among PWID. To reach and sustain HIV epidemic control, it will be necessary to maintain existing and implement new SSPs in combination with other prevention interventions.

Study protocol of a randomized controlled trial comparing two linkage models for HIV prevention and treatment in justice-involved persons

Background

Persons involved in the justice system are at high risk for HIV and drug overdose upon release to the community. This manuscript describes a randomized controlled trial of two evidence-based linkage interventions for provision of HIV prevention and treatment and substance use disorder (SUD) services in four high risk communities to assess which is more effective at addressing these needs upon reentry to the community from the justice system.

Methods

This is a 5-year hybrid type 1 effectiveness-implementation randomized controlled trial that compares two models (Patient Navigation [PN] or Mobile Health Unit [MHU] service delivery) of linking justice-involved individuals to the continuum of community-based HIV and SUD prevention and treatment service cascades of care. A total of 864 justice-involved individuals in four US communities with pre-arrest histories of opioid and/or stimulant use who are living with or at-risk of HIV will be randomized to receive either: (a) PN, wherein patient navigators will link study participants to community-based service providers; or (b) services delivered via an MHU, wherein study participants will be provided integrated HIV prevention/ treatment services and SUD services. The six-month post-release intervention will focus on access to pre-exposure prophylaxis (PrEP) for those without HIV and antiretroviral treatment (ART) for people living with HIV (PLH). Secondary outcomes will examine the continuum of PrEP and HIV care, including: HIV viral load, PrEP/ ART adherence; HIV risk behaviors; HCV testing and linkage to treatment; and sexually transmitted infection incidence and treatment. Additionally, opioid and other substance use disorder diagnoses, prescription, receipt, and retention on medication for opioid use disorder; opioid and stimulant use; and overdose will also be assessed. Primary implementation outcomes include feasibility, acceptability, sustainability, and costs required to implement and sustain the approaches as well as to scale-up in additional communities.

Discussion

Results from this project will help inform future methods of delivery of prevention, testing, and treatment of HIV, HCV, substance use disorders (particularly for opioids and stimulants), and sexually transmitted infections for justice-involved individuals in the community.

Trial registration: Clincialtrials.gov NCT05286879 March 18, 2022.

Primary case inference in viral outbreaks through analysis of intra-host variant population

Background

Investigation of outbreaks to identify the primary case is crucial for the interruption and prevention of transmission of infectious diseases. These individuals may have a higher risk of participating in near future transmission events when compared to the other patients in the outbreak, so directing more transmission prevention resources towards these individuals is a priority. Although the genetic characterization of intra-host viral populations can aid the identification of transmission clusters, it is not trivial to determine the directionality of transmissions during outbreaks, owing to complexity of viral evolution. Here, we present a new computational framework, PYCIVO: primary case inference in viral outbreaks. This framework expands upon our earlier work in development of QUENTIN, which builds a probabilistic disease transmission tree based on simulation of evolution of intra-host hepatitis C virus (HCV) variants between cases involved in direct transmission during an outbreak. PYCIVO improves upon QUENTIN by also adding a custom heterogeneity index and identifying the scenario when the primary case may have not been sampled.

Results

These approaches were validated using a set of 105 sequence samples from 11 distinct HCV transmission clusters identified during outbreak investigations, in which the primary case was epidemiologically verified. Both models can detect the correct primary case in 9 out of 11 transmission clusters (81.8%). However, while QUENTIN issues erroneous predictions on the remaining 2 transmission clusters, PYCIVO issues a null output for these clusters, giving it an effective prediction accuracy of 100%. To further evaluate accuracy of the inference, we created 10 modified transmission clusters in which the primary case had been removed. In this scenario, PYCIVO was able to correctly identify that there was no primary case in 8/10 (80%) of these modified clusters. This model was validated with HCV; however, this approach may be applicable to other microbial pathogens.

Conclusions

PYCIVO improves upon QUENTIN by also implementing a custom heterogeneity index which empowers PYCIVO to make the important ‘No primary case’ prediction. One or more samples, possibly including the primary case, may have not been sampled, and this designation is meant to account for these scenarios.

Performance evaluation of the Asante Rapid Recency Assay for verification of HIV diagnosis and detection of recent HIV-1 infections: Implications for epidemic control

We previously described development of a rapid test for recent infection (RTRI) that can diagnose HIV infection and detect HIV-1 recent infections in a single device. This technology was transferred to a commercial partner as Asante Rapid Recency Assay (ARRA). We evaluated performance of the ARRA kits in the laboratory using a well-characterized panel of specimens. The plasma specimen panel (N = 1500) included HIV-1 (N = 570), HIV-2 (N = 10), and HIV-negatives (N = 920) representing multiple subtypes and geographic locations. Reference diagnostic data were generated using the Bio-Rad HIV-1-2-O EIA/Western blot algorithm with further serotyping performed using the Multispot HIV-1/2 assay. The LAg-Avidity EIA was used to generate reference data on recent and long-term infection for HIV-1 positive specimens at a normalized optical density (ODn) cutoff of 2.0 corresponding to a mean duration of about 6 months. All specimens were tested with ARRA according to the manufacturer's recommendations. Test strips were also read for line intensities using a reader and results were correlated with visual interpretation. ARRA's positive verification line (PVL) correctly classified 575 of 580 HIV-positive and 910 of 920 negative specimens resulting in a sensitivity of 99.1% (95% CI: 98.0-99.6) and specificity of 98.9% (95% CI: 98.1-99.4), respectively. The reader-based classification was similar for PVL with sensitivity of 99.3% (576/580) and specificity of 98.8% (909/920). ARRA's long-term line (LTL) classified 109 of 565 HIV-1 specimens as recent and 456 as long-term compared to 98 as recent and 467 as long-term (LT) by LAg-Avidity EIA (cutoff ODn = 2.0), suggesting a mean duration of recent infection (MDRI) close to 6 months. Agreement of ARRA with LAg recent cases was 81.6% (80/98) and LT cases was 93.8% (438/467), with an overall agreement of 91.7% (kappa = 0.72). The reader (cutoff 2.9) classified 109/566 specimens as recent infections compared to 99 by the LAg-Avidity EIA for recency agreement of 81.8% (81/99), LT agreement of 9% (439/467) with overall agreement of 91.9% (kappa = 0.72). The agreement between visual interpretation and strip reader was 99.9% (95% CI: 99.6-99.9) for the PVL and 98.1% (95% CI: 96.6-98.9) for the LTL. ARRA performed well with HIV diagnostic sensitivity >99% and specificity >98%. Its ability to identify recent infections is comparable to the LA-Avidity EIA corresponding to an MDRI of about 6 months. This point-of-care assay has implications for real-time surveillance of new infections among newly diagnosed individuals for targeted prevention and interrupting ongoing transmission thus accelerating epidemic control.

Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China

HIV-1 CRF08_BC has become a major epidemic in heterosexuals and intravenous drug users (IDUs) in southern China. In order to evaluate the trends of its epidemic and facilitate targeted HIV prevention, we constructed the genetic transmission networks based on its pol sequences, derived from the National HIV Molecular Epidemiology Survey. Through retrospective network analysis, to study the epidemiological and demographic correlations with the transmission network. Of the 1,829 study subjects, 639 (34.9%) were clustered in 151 transmission networks. Factors associated with increased clustering include IDUs, heterosexual men, young adults and people with lower education (P < 0.05 for all). The IDUs, MSM, young adult and person with low education had more potential transmission links as well (P < 0.05 for all). The most crossover links were found between heterosexual women and IDUs, with 30.9% heterosexual women linked to IDUs. The crossover links heterosexual women were mainly those with middle age and single (P < 0.001). This study indicated that the HIV-1 CRF08_BC epidemic was still on going in China with more than one third of the infected people clustered in the transmission networks. Meanwhile, the study could help identify the active CRF08_BC spreader in the local community and greatly facilitate précising AIDS prevention with targeted intervention.

Identification of a Human Immunodeficiency Virus Type 1 and Neurosyphilis Cluster in Vermont

BACKGROUND

Rates of syphilis in the United States have more than doubled over the last several decades, largely among men who have sex with men (MSM). Our study characterizes a cluster of neurosyphilis cases among people with human immunodeficiency virus 1 (HIV-1) in Vermont in 2017-2018.

METHODS

Vermont Department of Health disease intervention specialists conduct interviews with newly diagnosed HIV-1 cases and pursue sexual networking analyses. Phylogenetic and network analyses of available Vermont HIV-1 polymerase (pol) sequences identified clusters of infection. Fishers-exact and independent t-tests were used to compare people with HIV-1 within or outside an identified cluster.

RESULTS

Between 1 January 2017 and 31 December 2018, 38 residents were diagnosed with HIV-1 infection. The mean age was 35.5 years, 79% were male and 82% were White. Risk factors for HIV-1 included MSM status (79%) and methamphetamine use (21%). Eighteen cases (49%) had HIV-1 viral loads (VLs) >100 000 copies/mL and 47% had CD4 cell counts <200/mm3. Eleven of the 38 (29%) had positive syphilis serology, including four (36%) with neurosyphilis. Sexual networking analysis revealed a ten-person cluster with higher VLs at diagnosis (90% with VLs > 100 000 copies/mL vs 33%, P = 0.015). Phylogenetic analysis of pol sequences showed a cluster of 14 cases with sequences that shared 98%-100% HIV-1 nucleotide identity.

CONCLUSIONS

This investigation of newly infected HIV-1 cases in Vermont led to identification of a cluster that appeared more likely to have advanced HIV-1 disease and neurosyphilis, supported by phylogenetic and network analyses.

Characteristics and growth of the genetic HIV transmission network of Mexico City during 2020

INTRODUCTION

Molecular surveillance systems could provide public health benefits to focus strategies to improve the HIV care continuum. Here, we infer the HIV genetic network of Mexico City in 2020, and identify actively growing clusters that could represent relevant targets for intervention.

METHODS

All new diagnoses, referrals from other institutions, as well as persons returning to care, enrolling at the largest HIV clinic in Mexico City were invited to participate in the study. The network was inferred from HIV pol sequences, using pairwise genetic distance methods, with a locally hosted, secure version of the HIV-TRACE tool: Seguro HIV-TRACE. Socio-demographic, clinical and behavioural metadata were overlaid across the network to design focused prevention interventions.

RESULTS

A total of 3168 HIV sequences from unique individuals were included. One thousand and one-hundred and fifty (36%) sequences formed 1361 links within 386 transmission clusters in the network. Cluster size varied from 2 to 14 (63% were dyads). After adjustment for covariates, lower age (adjusted odds ratio [aOR]: 0.37, p<0.001; >34 vs. <24 years), being a man who has sex with men (MSM) (aOR: 2.47, p = 0.004; MSM vs. cisgender women), having higher viral load (aOR: 1.28, p<0.001) and higher CD4+ T cell count (aOR: 1.80, p<0.001; ≥500 vs. <200 cells/mm3 ) remained associated with higher odds of clustering. Compared to MSM, cisgender women and heterosexual men had significantly lower education (none or any elementary: 59.1% and 54.2% vs. 16.6%, p<0.001) and socio-economic status (low income: 36.4% and 29.0% vs. 18.6%, p = 0.03) than MSM. We identified 10 (2.6%) clusters with constant growth, for prioritized intervention, that included intersecting sexual risk groups, highly connected nodes and bridge nodes between possible sub-clusters with high growth potential.

CONCLUSIONS

HIV transmission in Mexico City is strongly driven by young MSM with higher education level and recent infection. Nevertheless, leveraging network inference, we identified actively growing clusters that could be prioritized for focused intervention with demographic and risk characteristics that do not necessarily reflect the ones observed in the overall clustering population. Further studies evaluating different models to predict growing clusters are warranted. Focused interventions will have to consider structural and risk disparities between the MSM and the heterosexual populations.

HIV Cluster and Outbreak Detection and Response: The Science and Experience

The Respond pillar of the Ending the HIV Epidemic in the U.S. initiative, which consists of activities also known as cluster and outbreak detection and response, offers a framework to guide tailored implementation of proven HIV prevention strategies where transmission is occurring most rapidly. Cluster and outbreak response involves understanding the networks in which rapid transmission is occurring; linking people in the network to essential services; and identifying and addressing gaps in programs and services such as testing, HIV and other medical care, pre-exposure prophylaxis, and syringe services programs. This article reviews the experience gained through 30 HIV cluster and outbreak responses in North America during 2000-2020 to describe approaches for implementing these core response strategies. Numerous jurisdictions that have implemented these response strategies have demonstrated success in improving outcomes related to HIV care and viral suppression, testing, use of prevention services, and reductions in transmission or new diagnoses. Efforts to address important gaps in service delivery revealed by cluster and outbreak detection and response can strengthen prevention efforts broadly through multidisciplinary, multisector collaboration. In this way, the Respond pillar embodies the collaborative, data-guided approach that is critical to the overall success of the Ending the HIV Epidemic in the U.S. initiative.

Scale-Free Spanning Trees and Their Application in Genomic Epidemiology

We study the algorithmic problem of finding the most “scale-free-like” spanning tree of a connected graph. This problem is motivated by the fundamental problem of genomic epidemiology: given viral genomes sampled from infected individuals, reconstruct the transmission network (“who infected whom”). We use two possible objective functions for this problem and introduce the corresponding algorithmic problems termedm-SF (-scale free) ands-SF Spanning Tree problems. We prove that those problems are APX- and NP-hard, respectively, even in the classes of cubic and bipartite graphs. We propose two integer linear programming (ILP) formulations for thes-SF Spanning Tree problem, and experimentally assess its performance using simulated and experimental data. In particular, we demonstrate that the ILP-based approach allows for accurate reconstruction of transmission histories of several hepatitis C outbreaks.

MicrobeTrace: Retooling molecular epidemiology for rapid public health response

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.

Rapid advances in the fields of data science and bioinformatics have significantly improved molecular epidemiology tools used in public health and have led to major changes in the way outbreak investigation and pathogen transmission studies are conducted. However, the need for specialized computer skills often impedes the use of many of these tools in the public heath domain. We bridge this knowledge gap by development of an intuitive, standalone tool called MicrobeTrace to securely integrate, visualize and explore pathogen epidemiologic data. MicrobeTrace is an easy to use browser-based tool which can effectively merge contact tracing and/or microbial genomic data with demographic or behavioral information, resulting in elegant and informative networks as well as multiple customizable visualizations. MicrobeTrace can be used offline, with analyses being performed locally in the field, ensuring secure and confidential use of personally identifiable information (PII). We provide real world examples of how MicrobeTrace has been used in public health, including COVID outbreak investigations.

Incorporating metadata in HIV transmission network reconstruction: A machine learning feasibility assessment

HIV molecular epidemiology estimates the transmission patterns from clustering genetically similar viruses. The process involves connecting genetically similar genotyped viral sequences in the network implying epidemiological transmissions. This technique relies on genotype data which is collected only from HIV diagnosed and in-care populations and leaves many persons with HIV (PWH) who have no access to consistent care out of the tracking process. We use machine learning algorithms to learn the non-linear correlation patterns between patient metadata and transmissions between HIV-positive cases. This enables us to expand the transmission network reconstruction beyond the molecular network. We employed multiple commonly used supervised classification algorithms to analyze the San Diego Primary Infection Resource Consortium (PIRC) cohort dataset, consisting of genotypes and nearly 80 additional non-genetic features. First, we trained classification models to determine genetically unrelated individuals from related ones. Our results show that random forest and decision tree achieved over 80% in accuracy, precision, recall, and F1-score by only using a subset of meta-features including age, birth sex, sexual orientation, race, transmission category, estimated date of infection, and first viral load date besides genetic data. Additionally, both algorithms achieved approximately 80% sensitivity and specificity. The Area Under Curve (AUC) is reported 97% and 94% for random forest and decision tree classifiers respectively. Next, we extended the models to identify clusters of similar viral sequences. Support vector machine demonstrated one order of magnitude improvement in accuracy of assigning the sequences to the correct cluster compared to dummy uniform random classifier. These results confirm that metadata carries important information about the dynamics of HIV transmission as embedded in transmission clusters. Hence, novel computational approaches are needed to apply the non-trivial knowledge collected from inter-individual genetic information to metadata from PWH in order to expand the estimated transmissions. We note that feature extraction alone will not be effective in identifying patterns of transmission and will result in random clustering of the data, but its utilization in conjunction with genetic data and the right algorithm can contribute to the expansion of the reconstructed network beyond individuals with genetic data.

Methodological approaches for the prediction of opioid use-related epidemics in the United States: a narrative review and cross-disciplinary call to action

The opioid crisis in the United States has been defined by waves of drug- and locality-specific Opioid use-Related Epidemics (OREs) of overdose and bloodborne infections, among a range of health harms. The ability to identify localities at risk of such OREs, and better yet, to predict which ones will experience them, holds the potential to mitigate further morbidity and mortality. This narrative review was conducted to identify and describe quantitative approaches aimed at the "risk assessment," "detection" or "prediction" of OREs in the United States. We implemented a PubMed search composed of the: (1) objective (eg, prediction), (2) epidemiologic outcome (eg, outbreak), (3) underlying cause (ie, opioid use), (4) health outcome (eg, overdose, HIV), (5) location (ie, US). In total, 46 studies were included, and the following information extracted: discipline, objective, health outcome, drug/substance type, geographic region/unit of analysis, and data sources. Studies identified relied on clinical, epidemiological, behavioral and drug markets surveillance and applied a range of methods including statistical regression, geospatial analyses, dynamic modeling, phylogenetic analyses and machine learning. Studies for the prediction of overdose mortality at national/state/county and zip code level are rapidly emerging. Geospatial methods are increasingly used to identify hotspots of opioid use and overdose. In the context of infectious disease OREs, routine genetic sequencing of patient samples to identify growing transmission clusters via phylogenetic methods could increase early detection capacity. A coordinated implementation of multiple, complementary approaches would increase our ability to successfully anticipate outbreak risk and respond preemptively. We present a multi-disciplinary framework for the prediction of OREs in the US and reflect on challenges research teams will face in implementing such strategies along with good practices.

Broadly neutralizing antibody-mediated protection of macaques against repeated intravenous exposures to simian-human immunodeficiency virus

OBJECTIVE

The opioid epidemic has increased parentally acquired HIV infection. To inform the development of a long-acting prevention strategy, we evaluated the protective efficacy of broadly neutralizing antibodies (bNAbs) against intravenous simian-human immunodeficiency virus (SHIV) infection in macaques.

DESIGN

Five cynomolgus macaques were injected once subcutaneously with 10-1074 and 3BNC117 (10 mg each kg-1) and were repeatedly challenged intravenously once weekly with SHIVAD8-EO (130 TCID50), until infection was confirmed via plasma viral load assay. Two control macaques, which received no antibody, were challenged identically.

METHODS

Plasma viremia was monitored via RT-qPCR assay. bNAb concentrations were determined longitudinally in plasma samples via TZM-bl neutralization assays using virions pseudotyped with 10-1074-sensitive (X2088_c9) or 3BNC117-sensitive (Q769.d22) HIV envelope proteins.

RESULTS

Passively immunized macaques were protected against a median of five weekly intravenous SHIV challenges, as compared to untreated controls, which were infected following a single challenge. Of the two bNAbs, 10-1074 exhibited relatively longer persistence in vivo. The median plasma level of 10-1074 at SHIV breakthrough was 1.1 μg ml-1 (range: 0.6-1.6 μg ml-1), whereas 3BNC117 was undetectable. Probit modeling estimated that 6.6 μg ml-1 of 10-1074 in plasma corresponded to a 99% reduction in per-challenge infection probability, as compared to controls.

CONCLUSIONS

Significant protection against repeated intravenous SHIV challenges was observed following administration of 10-1074 and 3BNC117 and was due primarily to 10-1074. Our findings extend preclinical studies of bNAb-mediated protection against mucosal SHIV acquisition and support the possibility that intermittent subcutaneous injections of 10-1074 could serve as long-acting preexposure prophylaxis for persons who inject drugs.

Buprenorphine Increases HIV-1 Infection In Vitro but Does Not Reactivate HIV-1 from Latency

BACKGROUND

medication-assisted treatment (MAT) with buprenorphine is now widely prescribed to treat addiction to heroin and other illicit opioids. There is some evidence that illicit opioids enhance HIV-1 replication and accelerate AIDS pathogenesis, but the effect of buprenorphine is unknown.

METHODS

we obtained peripheral blood mononuclear cells (PBMCs) from healthy volunteers and cultured them in the presence of morphine, buprenorphine, or methadone. We infected the cells with a replication-competent CCR5-tropic HIV-1 reporter virus encoding a secreted nanoluciferase gene, and measured infection by luciferase activity in the supernatants over time. We also surveyed opioid receptor expression in PBMC, genital epithelial cells and other leukocytes by qPCR and western blotting. Reactivation from latency was assessed in J-Lat 11.1 and U1 cell lines.

RESULTS

we did not detect expression of classical opioid receptors in leukocytes, but did find nociception/orphanin FQ receptor (NOP) expression in blood and vaginal lymphocytes as well as genital epithelial cells. In PBMCs, we found that at physiological doses, morphine, and methadone had a variable or no effect on HIV infection, but buprenorphine treatment significantly increased HIV-1 infectivity (median: 8.797-fold increase with 20 nM buprenorphine, eight experiments, range: 3.570-691.9, p = 0.0078). Using latently infected cell lines, we did not detect reactivation of latent HIV following treatment with any of the opioid drugs.

CONCLUSIONS

our results suggest that buprenorphine, in contrast to morphine or methadone, increases the in vitro susceptibility of leukocytes to HIV-1 infection but has no effect on in vitro HIV reactivation. These findings contribute to our understanding how opioids, including those used for MAT, affect HIV infection and reactivation, and can help to inform the choice of MAT for people living with HIV or who are at risk of HIV infection.

Syphilis Testing as a Proxy Marker for a Subgroup of Men Who Have Sex With Men With a Central Role in HIV-1 Transmission in Guangzhou, China

Objectives: The objectives of this study were to distinguish the role of men who have sex with men (MSM) with or without syphilis testing in HIV-1 transmission and to provide molecular evidence of syphilis testing as a proxy marker for identifying the subgroup of MSM.

Methods: HIV-1 transmission clusters were constructed by HIV-TRACE and Cluster Picker using HIV-1 pol sequences from 729 newly diagnosed HIV-infected MSM from 2008 to 2012 in Guangzhou, China. The role of MSM in HIV-1 transmission networks was determined by a node influence measurement and centrality analysis. The association between syphilis testing and factors related to HIV-1 transmission and antiretroviral treatment (ART) were analyzed by the Cox regression model.

Results: Among HIV-infected MSM, 56.7% did not test for syphilis at the time of HIV-1 diagnosis. MSM without syphilis testing was a specific subgroup of MSM with a larger closeness centrality and clustering coefficient than the recipients of syphilis testing (P < 0.001), indicating their central position in the HIV-1 transmission networks. The median degree and radiality within HIV-1 transmission networks as well as the median K-shell scores were also greater for MSM without syphilis testing (P < 0.001), suggesting their relatively greater contribution in transmitting HIV-1 than the receipts of syphilis testing. MSM with syphilis testing usually did not disclose their occupation or were more likely to be unemployed or to take non-skilled jobs, to have a history of sexually transmitted infections (STIs), and to be AIDS patients when diagnosed with HIV-1 infection (P < 0.05). Multivariable Cox regression analysis indicated that syphilis testing per se did not promote the engagement of ART (P = 0.233) or affect the speed of CD4⁺ T cell count recovery after treatment (P = 0.256).

Conclusions: Our study identifies syphilis testing as a proxy marker of a specific subgroup of HIV-infected MSM who refuse syphilis testing during HIV-1 diagnosis with an important role in HIV-1 transmission. Specific prevention and intervention targeting MSM without syphilis testing during HIV-1 care are urgently needed.

HIV-1 Tat and Morphine Differentially Disrupt Pyramidal Cell Structure and Function and Spatial Learning in Hippocampal Area CA1: Continuous versus Interrupted Morphine Exposure

About half the people infected with human immunodeficiency virus (HIV) have neurocognitive deficits that often include memory impairment and hippocampal deficits, which can be exacerbated by opioid abuse. To explore the effects of opioids and HIV on hippocampal CA1 pyramidal neuron structure and function, we induced HIV-1 transactivator of transcription (Tat) expression in transgenic mice for 14 d and co-administered time-release morphine or vehicle subcutaneous implants during the final 5 d (days 9-14) to establish steady-state morphine levels. Morphine was withheld from some ex vivo slices during recordings to begin to assess the initial pharmacokinetic consequences of opioid withdrawal. Tat expression reduced hippocampal CA1 pyramidal neuronal excitability at lower stimulating currents. Pyramidal cell firing rates were unaffected by continuous morphine exposure. Behaviorally, exposure to Tat or high dosages of morphine impaired spatial memory Exposure to Tat and steady-state levels of morphine appeared to have largely independent effects on pyramidal neuron structure and function, a response that is distinct from other vulnerable brain regions such as the striatum. By contrast, acutely withholding morphine (from morphine-tolerant ex vivo slices) revealed unique and selective neuroadaptive shifts in CA1 pyramidal neuronal excitability and dendritic plasticity, including some interactions with Tat. Collectively, the results show that opioid-HIV interactions in hippocampal area CA1 are more nuanced than previously assumed, and appear to vary depending on the outcome assessed and on the pharmacokinetics of morphine exposure.

Difference in HIV testing behavior by injection status, among users of illicit drugs

Human Immunodeficiency Virus (HIV) infection remains prevalent among the marginalized and drug using population in the United States. Testing for HIV is an important and cost-effective way to reduce HIV prevalence. Our objective was to determine if there is a difference in the number of HIV testing by injection status among users of illicit drugs and if a person's social network characteristics is a contributing factor. Using a cross-sectional design and negative binomial regression models, we assessed HIV testing behavior of people who use non-injected drugs (PWND) compared to people who use injected drugs (PWID). In an analytic sample of 539 participants, PWND tested for HIV 19% less compared to PWID, PR (95% CI) = 0.81 (0.66, 0.98), p = 0.03. Other contributing factors of testing were education, condomless sex, STIs, heroin use, and participant's sex network. The interaction term between PWND and emotional support in relation to HIV testing was significant, 1.33 (1.03, 1.69), p=0.03. These findings suggest HIV testing behavior differed by injection status, and this relationship may be dependent on emotional support. To exert a greater impact on the HIV epidemic, interventions and policies encouraging HIV testing in PWND, an understudied at-risk sub-population, are warranted.

Geographic Distribution of HIV Transmission Networks in the United States

BACKGROUND

Understanding geographic patterns of HIV transmission is critical to designing effective interventions. We characterized geographic proximity by transmission risk and urban-rural characteristics among people with closely related HIV strains suggestive of potential transmission relationships.

METHODS

We analyzed US National HIV Surveillance System data of people diagnosed between 2010 and 2016 with a reported HIV-1 partial polymerase nucleotide sequence. We used HIV TRAnsmission Cluster Engine (HIV-TRACE) to identify sequences linked at a genetic distance of ≤0.5%. For each linked person, we assessed median distances between counties of residence at diagnosis by transmission category and urban-rural classification, weighting observations to account for persons with multiple linked sequences.

RESULTS

There were 24,743 persons with viral sequence linkages to at least one other person included in this analysis. Overall, half (50.9%) of persons with linked viral sequences resided in different counties, and the median distance from persons with linked viruses was 11 km/7 miles [interquartile range (IQR), 0-145 km/90 miles]. Median distances were highest for men who have sex with men (MSM: 14 km/9 miles; IQR, 0-179 km/111 miles) and MSM who inject drugs, and median distances increased with increasing rurality (large central metro: 0 km/miles; IQR, 0-83 km/52 miles; nonmetro: 103 km/64 miles; IQR, 40 km/25 miles-316 km/196 miles).

CONCLUSION

Transmission networks in the United States involving MSM, MSM who inject drugs, or persons living in small metro and nonmetro counties may be more geographically dispersed, highlighting the importance of coordinated health department efforts for comprehensive follow-up and linkage to care.

Human Immunodeficiency Virus (HIV) Outbreak Investigation Among Persons Who Inject Drugs in Massachusetts Enhanced by HIV Sequence Data

BACKGROUND

The Massachusetts Department of Public Health and the Centers for Disease Control and Prevention collaborated to characterize a human immunodeficiency virus (HIV) outbreak in northeastern Massachusetts and prevent further transmission. We determined the contributions of HIV sequence data to defining the outbreak.

METHODS

Human immunodeficiency virus surveillance and partner services data were analyzed to understand social and molecular links within the outbreak. Cases were defined as HIV infections diagnosed during 2015-2018 among people who inject drugs with connections to northeastern Massachusetts or HIV infections among other persons named as partners of a case or whose HIV polymerase sequence linked to another case, regardless of diagnosis date or geography.

RESULTS

Of 184 cases, 65 (35%) were first identified as part of the outbreak through molecular analysis. Twenty-nine cases outside of northeastern Massachusetts were molecularly linked to the outbreak. Large molecular clusters (75, 28, and 11 persons) were identified. Among 161 named partners, 106 had HIV; of those, 40 (38%) diagnoses occurred through partner services.

CONCLUSIONS

Human immunodeficiency virus sequence data increased the case count by 55% and expanded the geographic scope of the outbreak. Human immunodeficiency virus sequence and partner services data each identified cases that the other method would not have, maximizing prevention and care opportunities for HIV-infected persons and their partners.

Using molecular transmission networks to understand the epidemic characteristics of HIV-1 CRF08_BC across China

HIV-1 CRF08_BC has become a major epidemic in heterosexuals and intravenous drug users (IDUs) in southern China. In order to evaluate the trends of its epidemic and facilitate targeted HIV prevention, we constructed the genetic transmission networks based on its pol sequences, derived from the National HIV Molecular Epidemiology Survey. Through retrospective network analysis, to study the epidemiological and demographic correlations with the transmission network. Of the 1,829 study subjects, 639 (34.9%) were clustered in 151 transmission networks. Factors associated with increased clustering include IDUs, heterosexual men, young adults and people with lower education (P < 0.05 for all). The IDUs, MSM, young adult and person with low education had more potential transmission links as well (P < 0.05 for all). The most crossover links were found between heterosexual women and IDUs, with 30.9% heterosexual women linked to IDUs. The crossover links heterosexual women were mainly those with middle age and single (P < 0.001). This study indicated that the HIV-1 CRF08_BC epidemic was still on going in China with more than one third of the infected people clustered in the transmission networks. Meanwhile, the study could help identify the active CRF08_BC spreader in the local community and greatly facilitate précising AIDS prevention with targeted intervention.

Drug Injection-Related Norms and High-Risk Behaviors of People Who Inject Drugs in Athens, Greece

Drug use involves social interactions. Therefore, norms in the proximal environment of people who inject drugs (PWID) can favor behaviors that may result in HIV transmission. This work aimed at studying drug injection-related norms and their potential association with risky behaviors among PWID in Athens, Greece, in the context of economic recession and political activism that followed the fiscal crisis and soon after a recent HIV outbreak had leveled off. The Transmission Reduction Intervention Project (TRIP) was a social network-based approach (June 2013 to July 2015) that involved two groups of PWID seeds-with recent HIV infection and with long-term HIV infection and one control group of HIV-negative PWID. Network contacts of seeds were also enrolled. TRIP participants answered a questionnaire that included items on injection-related norms and behaviors. TRIP recruited 320 PWID (HIV positive, 44.4%). TRIP participants, especially those without HIV, often recalled or perceived as normative among their partners and in their networks some behaviors that can lead to HIV transmission. TRIP participants who recalled that they were encouraged by their regular drug partners to use an unclean syringe were almost twice as likely to report that they share syringes [odds ratio (OR) = 2.03; 95% confidence interval (CI) = 1.86-2.21], or give syringes to someone else (OR = 1.70; 95% CI = 1.42-2.04) as those who did not recall such an encouragement. Associations were modified by HIV status. HIV negatives, who were reportedly encouraged to share nonsyringe injecting equipment, were almost 4.5 times as likely to share that material as HIV-negative participants who were not encouraged (OR = 4.59, 95% CI = 4.12-5.11). Further research is needed on the multiple determinants (social, economic, and political) of norms in the social environments of PWID. Since peer norms are associated with risky behaviors, interventions should be developed to encourage norms and peer pressure against the sharing of injection equipment.

A review of network simulation models of hepatitis C virus and HIV among people who inject drugs

Network modelling is a valuable tool for simulating hepatitis C virus (HCV) and HIV transmission among people who inject drugs (PWID) and assessing the potential impact of treatment and harm-reduction interventions. In this paper, we review literature on network simulation models, highlighting key structural considerations and questions that network models are well suited to address. We describe five approaches (Erdös-Rényi, Stochastic Block, Watts-Strogatz, Barabási-Albert, and Exponential Random Graph Model) used to model partnership formation with emphasis on the strengths of each approach in simulating different features of real-world PWID networks. We also review two important structural considerations when designing or interpreting results from a network simulation study: (1) dynamic vs. static network and (2) injection only vs. both injection and sexual networks. Dynamic network simulations allow partnerships to evolve and disintegrate over time, capturing corresponding shifts in individual and population-level risk behaviour; however, their high level of complexity and reliance on difficult-to-observe data has driven others to develop static network models. Incorporating both sexual and injection partnerships increases model complexity and data demands, but more accurately represents HIV transmission between PWID and their sexual partners who may not also use drugs. Network models add the greatest value when used to investigate how leveraging network structure can maximize the effectiveness of health interventions and optimize investments. For example, network models have shown that features of a given network and epidemic influence whether the greatest community benefit would be achieved by allocating hepatitis C or HIV treatment randomly, versus to those with the most partners. They have also demonstrated the potential for syringe services and "buddy sharing" programs to reduce disease transmission.

Epidemiological data analysis of viral quasispecies in the next-generation sequencing era

The unprecedented coverage offered by next-generation sequencing (NGS) technology has facilitated the assessment of the population complexity of intra-host RNA viral populations at an unprecedented level of detail. Consequently, analysis of NGS datasets could be used to extract and infer crucial epidemiological and biomedical information on the levels of both infected individuals and susceptible populations, thus enabling the development of more effective prevention strategies and antiviral therapeutics. Such information includes drug resistance, infection stage, transmission clusters and structures of transmission networks. However, NGS data require sophisticated analysis dealing with millions of error-prone short reads per patient. Prior to the NGS era, epidemiological and phylogenetic analyses were geared toward Sanger sequencing technology; now, they must be redesigned to handle the large-scale NGS datasets and properly model the evolution of heterogeneous rapidly mutating viral populations. Additionally, dedicated epidemiological surveillance systems require big data analytics to handle millions of reads obtained from thousands of patients for rapid outbreak investigation and management. We survey bioinformatics tools analyzing NGS data for (i) characterization of intra-host viral population complexity including single nucleotide variant and haplotype calling; (ii) downstream epidemiological analysis and inference of drug-resistant mutations, age of infection and linkage between patients; and (iii) data collection and analytics in surveillance systems for fast response and control of outbreaks.

Molecular Epidemiological Analysis of the Origin and Transmission Dynamics of the HIV-1 CRF01_AE Sub-Epidemic in Bulgaria

HIV-1 subtype CRF01_AE is the second most predominant strain in Bulgaria, yet little is known about the molecular epidemiology of its origin and transmissibility. We used a phylodynamics approach to better understand this sub-epidemic by analyzing 270 HIV-1 polymerase (pol) sequences collected from persons diagnosed with HIV/AIDS between 1995 and 2019. Using network analyses at a 1.5% genetic distance threshold (d), we found a large 154-member outbreak cluster composed mostly of persons who inject drugs (PWID) that were predominantly men. At d = 0.5%, which was used to identify more recent transmission, the large cluster dissociated into three clusters of 18, 12, and 7 members, respectively, five dyads, and 107 singletons. Phylogenetic analysis of the Bulgarian sequences with publicly available global sequences showed that CRF01_AE likely originated from multiple Asian countries, with Vietnam as the likely source of the outbreak cluster between 1988 and 1990. Our findings indicate that CRF01_AE was introduced into Bulgaria multiple times since 1988, and infections then rapidly spread among PWID locally with bridging to other risk groups and countries. CRF01_AE continues to spread in Bulgaria as evidenced by the more recent large clusters identified at d = 0.5%, highlighting the importance of public health prevention efforts in the PWID communities.

Implementation of Syringe Services Programs to Prevent Rapid Human Immunodeficiency Virus Transmission in Rural Counties in the United States: A Modeling Study

BACKGROUND

Syringe services programs (SSPs) are effective venues for delivering harm-reduction services to people who inject drugs (PWID). However, SSPs often face significant barriers to implementation, particularly in the absence of known human immunodeficiency virus (HIV) outbreaks.

METHODS

Using an agent-based model, we simulated HIV transmission in Scott County, Indiana, a rural county with a 1.7% prevalence of injection drug use. We compared outcomes arising in the absence of an SSP, in the presence of a pre-existing SSP, and with implementation of an SSP after the detection of an HIV outbreak among PWID over 5 years following the introduction of a single infection into the network.

RESULTS

In the absence of an SSP, the model predicted an average of 176 infections among PWID over 5 years or an incidence rate of 12.1/100 person-years. Proactive implementation averted 154 infections and decreased incidence by 90.3%. With reactive implementation beginning operations 10 months after the first infection, an SSP would prevent 107 infections and decrease incidence by 60.8%. Reductions in incidence were also observed among people who did not inject drugs.

CONCLUSIONS

Based on model predictions, proactive implementation of an SSP in Scott County had the potential to avert more HIV infections than reactive implementation after the detection of an outbreak. The predicted impact of reactive SSP implementation was highly dependent on timely implementation after detecting the earliest infections. Consequently, there is a need for expanded proactive SSP implementation in the context of enhanced monitoring of outbreak vulnerability in Scott County and similar rural contexts.

Network structure and rapid HIV transmission among people who inject drugs: A simulation-based analysis

As HIV incidence among people who inject drugs grows in the context of an escalating drug overdose epidemic in North America, investigating how network structure may affect vulnerability to rapid HIV transmission is necessary for preventing outbreaks. We compared the characteristics of the observed contact tracing network from the 2015 outbreak in rural Indiana with 1000 networks generated by an agent-based network model with approximately the same number of individuals (n = 420) and ties between them (n = 913). We introduced an initial HIV infection into the simulated networks and compared the subsequent epidemic behavior (e.g., cumulative HIV infections over 5 years). The model was able to produce networks with largely comparable characteristics and total numbers of incident HIV infections. Although the model was unable to produce networks with comparable cohesiveness (where the observed network had a transitivity value 35.7 standard deviations from the mean of the simulated networks), the structural variability of the simulated networks allowed for investigation into their potential facilitation of HIV transmission. These findings emphasize the need for continued development of injection network simulation studies in tandem with empirical data collection to further investigate how network characteristics played a role in this and future outbreaks.

Epidemiological and time series analysis on the incidence and death of AIDS and HIV in China

Background

To investigate the regional and age-specific distribution of AIDS/HIV in China from 2004 to 2017 and to conduct time series analysis of the epidemiological trends.

Method

Using official surveillance data from publicly accessible database of the national infectious disease reporting system, we described long-term patterns of incidence and death in AIDS/HIV, analyzed age group and regional epidemic characteristics, and established Autoregressive Integrated Moving Average (ARIMA) models for time series analysis.

Result

The incidence and death of AIDS/HIV have increased rapidly from 2004 to 2017, with significant difference regarding age groups and provincial regions (a few provinces appear as hot spots). With goodness-of-fit criteria and using data from 2004 to 2015, ARIMA (0,1,3) × (2,0,0), ARIMA (3,1,0) × (1,0,1), and ARIMA (0,1,2) × (2,0,0) were chosen as the optimal model for the incidence of AIDS, HIV, and combined; ARIMA (0,1,3) × (1,0,0) was chosen as the optimal model for the death of AIDS, HIV, and combined. ARIMA models robustly predicted the incidence and death of AIDS/HIV in 2016 and 2017.

Conclusion

A focused intervention strategy targeting specific regions and age groups is essential for the prevention and control of AIDS/HIV. ARIMA models function as data-driven and evidence-based methods to forecast the trends of infectious diseases and formulate public health policies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-020-09977-8.