Tracking external introductions of HIV using phylodynamics reveals a major source of infections in rural KwaZulu-Natal, South Africa

Leveraging insect-specific viruses to elucidate mosquito population structure and dynamics

Several aspects of mosquito ecology that are important for vectored disease transmission and control have been difficult to measure at epidemiologically important scales in the field. In particular, the ability to describe mosquito population structure and movement rates has been hindered by difficulty in quantifying fine-scale genetic variation among populations. The mosquito virome represents a possible avenue for quantifying population structure and movement rates across multiple spatial scales. Mosquito viromes contain a diversity of viruses, including several insect-specific viruses (ISVs) and "core" viruses that have high prevalence across populations. To date, virome studies have focused on viral discovery and have only recently begun examining viral ecology. While nonpathogenic ISVs may be of little public health relevance themselves, they provide a possible route for quantifying mosquito population structure and dynamics. For example, vertically transmitted viruses could behave as a rapidly evolving extension of the host's genome. It should be possible to apply established analytical methods to appropriate viral phylogenies and incidence data to generate novel approaches for estimating mosquito population structure and dispersal over epidemiologically relevant timescales. By studying the virome through the lens of spatial and genomic epidemiology, it may be possible to investigate otherwise cryptic aspects of mosquito ecology. A better understanding of mosquito population structure and dynamics are key for understanding mosquito-borne disease ecology and methods based on ISVs could provide a powerful tool for informing mosquito control programs.

Population-level viremia predicts HIV incidence at the community level across the Universal Testing and Treatment Trials in eastern and southern Africa

Universal HIV testing and treatment (UTT) strategies aim to optimize population-level benefits of antiretroviral treatment. Between 2012 and 2018, four large community randomized trials were conducted in eastern and southern Africa. While their results were broadly consistent showing decreased population-level viremia reduces HIV incidence, it remains unclear how much HIV incidence can be reduced by increasing suppression among people living with HIV (PLHIV). We conducted a pooled analysis across the four UTT trials. Leveraging data from 105 communities in five countries, we evaluated the linear relationship between i) population-level viremia (prevalence of non-suppression-defined as plasma HIV RNA >500 or >400 copies/mL-among all adults, irrespective of HIV status) and HIV incidence; and ii) prevalence of non-suppression among PLHIV and HIV incidence, using parametric g-computation. HIV prevalence, measured in 257 929 persons, varied from 2 to 41% across the communities; prevalence of non-suppression among PLHIV, measured in 31 377 persons, from 3 to 70%; population-level viremia, derived from HIV prevalence and non-suppression, from < 1% to 25%; and HIV incidence, measured over 345 844 person-years (PY), from 0.03/100PY to 3.46/100PY. Decreases in population-level viremia were strongly associated with decreased HIV incidence in all trials (between 0.45/100PY and 1.88/100PY decline in HIV incidence per 10 percentage points decline in viremia). Decreases in non-suppression among PLHIV were also associated with decreased HIV incidence in all trials (between 0.06/100PY and 0.17/100PY decline in HIV incidence per 10 percentage points decline in non-suppression). Our results support both the utility of population-level viremia as a predictor of incidence, and thus a tool for targeting prevention interventions, and the ability of UTT approaches to reduce HIV incidence by increasing viral suppression. Implementation of universal HIV testing approaches, coupled with interventions to leverage linkage to treatment, adapted to local contexts, can reduce HIV acquisition at population level.

Combining molecular network analysis and field epidemiology to quantify local HIV transmission and highlight ongoing epidemics

OBJECTIVES

This study aimed to establish a collaborative approach to quantify local HIV transmission, which is an issue of great concern to public health.

METHODS

We linked HIV-1 pol gene sequences to demographic information and epidemiological investigations in Hangzhou (a central city in East China). We estimated local acquisition rates from a collaboration of molecular network analysis (with a distance-based approach) and epidemiological investigations.

RESULTS

Among 1064 newly diagnosed patients with HIV, 857 pol sequences were acquired and subsequently analyzed. Multiple subtypes were identified, with circulating recombinant form (CRF)07_BC (42.5%) and CRF01_AE (39.2%) predominating, followed by 13 other subtypes and 26 unique recombinant forms. By integrating the molecular network analysis and epidemiological investigations, we estimated that the proportion of local infection was 63.2%. The multivariable analyses revealed that individuals in clusters were more likely to be local residents, be aged 50 years or older, work as farmers, and have a higher first cluster of differentiation 4 count level (P <0.05). The proportions of local acquisitions over 70% were observed in local residents (79.9%, 242/303), individuals aged 50 years or older (73.6%, 181/246), and farmers (75.6%, 99/131).

CONCLUSION

The molecular network analysis can augment traditional HIV epidemic surveillance. This study establishes a paradigm for quantifying local HIV transmission for generalization in other areas.

Tracing the origin of an imported HIV-1 sub-subtype A6 strain first identified in Zhejiang Province, China

Human migration and mobility have been identified as key drivers of HIV dissemination among nations, which increases the problem of genetic diversity. Here, we report the near full-length genome of HIV-1 A6 identified in a female patient in the remote mountain area of Lishui, Zhejiang Province, which is the first time A6 has been reported in China. The near full-length genome was amplified with two large amplicons of 5.5 kb and 3.7 kb, and then target PCR products were sequenced by Sanger sequencing. The A6 strain was confirmed by the Basic Local Alignment Search Tool (BLAST) and a maximum-likelihood (ML) phylogenetic tree. The time to the most recent common ancestor (tMRCA) was inferred to be 2004 (95% HPD interval: 2003-2006). The sequence harbored the L74I mutation, which is a key characteristic genetic marker of A6. Combining the above evidence with epidemiological investigations, this A6 strain was determined to be from Ukraine, which was supported by phylogenetic analysis. This study identified a foreign imported strain, indicating a trend of increasing complication in the HIV-1 epidemic in Zhejiang, China.

Industrial mining and HIV risk: evidence from 39 mine openings across 16 countries in sub-Saharan Africa

OBJECTIVES

The aim of this study was to assess the impact of natural resource extraction projects on HIV transmission risks in local communities in sub-Saharan Africa.

DESIGN

Difference-in-differences design using repeated cross-sectional data from around newly opened mines.

METHODS

We combined data on mine openings with HIV data from the Demographic and Health Surveys (DHS). Using logistic regression models, we compared HIV-related indicators between mining (i.e. up to 10 km distance from the mine) and comparison (i.e. 10-50 km) areas before and after mine opening to identify their impact on HIV prevalence, sexual behavior and HIV knowledge.

RESULTS

A total of 33 086 individuals across 39 mine openings were analyzed. Adjusting for baseline differences and temporal trends in the study regions, mine opening increased the odds of HIV infection almost two-fold [odds ratio (OR): 1.93, 95% confidence interval (CI): 1.19-3.14]. Strongest effects were seen in high-prevalence countries and in the 20-29 years age group. In mining communities around operational mines, there was a tendency towards lower HIV knowledge (OR: 0.81, 95% CI: 0.63-1.04). New mine openings increased the odds of risky sexual behaviors, such as having multiple sex partners (OR: 1.61, 95% CI: 1.02-2.55), high-risk sexual partners (OR: 1.45, 95% CI: 1.03-2.05) and unprotected sex with high-risk partners (OR: 1.77, 95% CI: 1.18-2.67).

CONCLUSION

The findings suggest that in our sample of households surrounding industrial mines, HIV infection risks substantially increase upon mine opening. Existing strategies for addressing mining-related risks for HIV transmission seem to be insufficient. Further efforts for mitigating and monitoring impacts of mines are needed.

Evaluating whole HIV-1 genome sequence for estimation of incidence and migration in a rural South African community

Background: South Africa has the largest number of people living with HIV (PLWHIV) in the world, with HIV prevalence and transmission patterns varying greatly between provinces. Transmission between regions is still poorly understood, but phylodynamics of HIV-1 evolution can reveal how many infections are attributable to contacts outside a given community. We analysed whole genome HIV-1 genetic sequences to estimate incidence and the proportion of transmissions between communities in Hlabisa, a rural South African community. Methods: We separately analysed HIV-1 for gag, pol, and env genes sampled from 2,503 PLWHIV. We estimated time-scaled phylogenies by maximum likelihood under a molecular clock model. Phylodynamic models were fitted to time-scaled trees to estimate transmission rates, effective number of infections, incidence through time, and the proportion of infections imported to Hlabisa. We also partitioned time-scaled phylogenies with significantly different distributions of coalescent times. Results: Phylodynamic analyses showed similar trends in epidemic growth rates between 1980 and 1990. Model-based estimates of incidence and effective number of infections were consistent across genes. Parameter estimates with gag were generally smaller than those estimated with pol and env. When estimating the proportions of new infections in Hlabisa from immigration or transmission from external sources, our posterior median estimates were 85% (95% credible interval (CI) = 78%–92%) for gag, 62% (CI = 40%–78%) for pol, and 77% (CI = 58%–90%) for env in 2015. Analysis of phylogenetic partitions by gene showed that most close global reference sequences clustered within a single partition. This suggests local evolving epidemics or potential unmeasured heterogeneity in the population. Conclusions: We estimated consistent epidemic dynamic trends for gag, pol and env genes using phylodynamic models. There was a high probability that new infections were not attributable to endogenous transmission within Hlabisa, suggesting high inter-connectedness between communities in rural South Africa.

Integrating animal movements with phylogeography to model the spread of PRRSV in the USA

Viral sequence data coupled with phylodynamic models have become instrumental in investigating the outbreaks of human and animal diseases, and the incorporation of the hypothesized drivers of pathogen spread can enhance the interpretation from phylodynamic inference. Integrating animal movement data with phylodynamics allows us to quantify the extent to which the spatial diffusion of a pathogen is influenced by animal movements and contrast the relative importance of different types of movements in shaping pathogen distribution. We combine animal movement, spatial, and environmental data in a Bayesian phylodynamic framework to explain the spatial diffusion and evolutionary trends of a rapidly spreading sub-lineage (denoted L1A) of porcine reproductive and respiratory syndrome virus (PRRSV) Type 2 from 2014 to 2017. PRRSV is the most important endemic pathogen affecting pigs in the USA, and this particular virulent sub-lineage emerged in 2014 and continues to be the dominant lineage in the US swine industry to date. Data included 984 open reading frame 5 (ORF5) PRRSV L1A sequences obtained from two production systems in a swine-dense production region (∼85,000 mi²) in the USA between 2014 and 2017. The study area was divided into sectors for which model covariates were summarized, and animal movement data between each sector were summarized by age class (wean: 3–4 weeks; feeder: 8–25 weeks; breeding: ≥21 weeks). We implemented a discrete-space phylogeographic generalized linear model using Bayesian evolutionary analysis by sampling trees (BEAST) to infer factors associated with variability in between-sector diffusion rates of PRRSV L1A. We found that between-sector spread was enhanced by the movement of feeder pigs, spatial adjacency of sectors, and farm density in the destination sector. The PRRSV L1A strain was introduced in the study area in early 2013, and genetic diversity and effective population size peaked in 2015 before fluctuating seasonally (peaking during the summer months). Our study underscores the importance of animal movements and shows, for the first time, that the movement of feeder pigs (8–25 weeks old) shaped the spatial patterns of PRRSV spread much more strongly than the movements of other age classes of pigs. The inclusion of movement data into phylodynamic models as done in this analysis may enhance our ability to identify crucial pathways of disease spread that can be targeted to mitigate the spatial spread of infectious human and animal pathogens.

PopART-IBM, a highly efficient stochastic individual-based simulation model of generalised HIV epidemics developed in the context of the HPTN 071 (PopART) trial

Mathematical models are powerful tools in HIV epidemiology, producing quantitative projections of key indicators such as HIV incidence and prevalence. In order to improve the accuracy of predictions, such models need to incorporate a number of behavioural and biological heterogeneities, especially those related to the sexual network within which HIV transmission occurs. An individual-based model, which explicitly models sexual partnerships, is thus often the most natural type of model to choose. In this paper we present PopART-IBM, a computationally efficient individual-based model capable of simulating 50 years of an HIV epidemic in a large, high-prevalence community in under a minute. We show how the model calibrates within a Bayesian inference framework to detailed age- and sex-stratified data from multiple sources on HIV prevalence, awareness of HIV status, ART status, and viral suppression for an HPTN 071 (PopART) study community in Zambia, and present future projections of HIV prevalence and incidence for this community in the absence of trial intervention.

In this paper we present PopART-IBM, an individual-based model used to simulate HIV transmission in communities in high prevalence settings. We show that PopART-IBM can simulate transmission over a span of decades in a large community in less than a minute. This computational efficiency allows us to calibrate the model within an inference framework, and we show an illustrative example of calibration using an adaptive population Monte Carlo Approximate Bayesian Computation algorithm for a community in Zambia that was part of the HPTN-071 (PopART) trial. We compare the detailed model output to real-world data collected during the trial from this community. Finally, we project how the HIV epidemic would have changed over time in this community if no intervention from the trial had occurred.

The Role of Phylogenetics in Discerning HIV-1 Mixing among Vulnerable Populations and Geographic Regions in Sub-Saharan Africa: A Systematic Review

To reduce global HIV-1 incidence, there is a need to understand and disentangle HIV-1 transmission dynamics and to determine the geographic areas and populations that act as hubs or drivers of HIV-1 spread. In Sub-Saharan Africa (sSA), the region with the highest HIV-1 burden, information about such transmission dynamics is sparse. Phylogenetic inference is a powerful method for the study of HIV-1 transmission networks and source attribution. In this review, we assessed available phylogenetic data on mixing between HIV-1 hotspots (geographic areas and populations with high HIV-1 incidence and prevalence) and areas or populations with lower HIV-1 burden in sSA. We searched PubMed and identified and reviewed 64 studies on HIV-1 transmission dynamics within and between risk groups and geographic locations in sSA (published 1995-2021). We describe HIV-1 transmission from both a geographic and a risk group perspective in sSA. Finally, we discuss the challenges facing phylogenetic inference in mixed epidemics in sSA and offer our perspectives and potential solutions to the identified challenges.

Using mobile phone data to reveal risk flow networks underlying the HIV epidemic in Namibia

Twenty-six million people are living with HIV in sub-Saharan Africa; epidemics are widely dispersed, due to high levels of mobility. However, global elimination strategies do not consider mobility. We use Call Detail Records from 9 billion calls/texts to model mobility in Namibia; we quantify the epidemic-level impact by using a mathematical framework based on spatial networks. We find complex networks of risk flows dispersed risk countrywide: increasing the risk of acquiring HIV in some areas, decreasing it in others. Overall, 40% of risk was mobility-driven. Networks contained multiple risk hubs. All constituencies (administrative units) imported and exported risk, to varying degrees. A few exported very high levels of risk: their residents infected many residents of other constituencies. Notably, prevalence in the constituency exporting the most risk was below average. Large-scale networks of mobility-driven risk flows underlie generalized HIV epidemics in sub-Saharan Africa. In order to eliminate HIV, it is likely to become increasingly important to implement innovative control strategies that focus on disrupting risk flows.

Development of a Dissemination Platform for Spatiotemporal and Phylogenetic Analysis of Avian Infectious Bronchitis Virus

Infecting large portions of the global poultry populations, the avian infectious bronchitis virus (IBV) remains a major economic burden in North America. With more than 30 serotypes globally distributed, Arkansas, Connecticut, Delaware, Georgia, and Massachusetts are among the most predominant serotypes in the United States. Even though vaccination is widely used, the high mutation rate exhibited by IBV is continuously triggering the emergence of new viral strains and hindering control and prevention measures. For that reason, targeted strategies based on constantly updated information on the IBV circulation are necessary. Here, we sampled IBV-infected farms from one US state and collected and analyzed 65 genetic sequences coming from three different lineages along with the immunization information of each sampled farm. Phylodynamic analyses showed that IBV dispersal velocity was 12.3 km/year. The majority of IBV infections appeared to have derived from the introduction of the Arkansas DPI serotype, and the Arkansas DPI and Georgia 13 were the predominant serotypes. When analyzed against IBV sequences collected across the United States and deposited in the GenBank database, the most likely viral origin of our sequences was from the states of Alabama, Georgia, and Delaware. Information about vaccination showed that the MILDVAC-MASS+ARK vaccine was applied on 26% of the farms. Using a publicly accessible open-source tool for real-time interactive tracking of pathogen spread and evolution, we analyzed the spatiotemporal spread of IBV and developed an online reporting dashboard. Overall, our work demonstrates how the combination of genetic and spatial information could be used to track the spread and evolution of poultry diseases, providing timely information to the industry. Our results could allow producers and veterinarians to monitor in near-real time the current IBV strain circulating, making it more informative, for example, in vaccination-related decisions.

Acquisition and transmission of HIV-1 among migrants and Chinese in Guangzhou, China from 2008 to 2012: Phylogenetic analysis of surveillance data

BACKGROUND

Post-migration infection and domestic transmission of HIV-1 between immigrants and local population are critical for the HIV epidemic, but have not been addressed thus far in China.

METHODS

Transmission clusters were analyzed with two cluster reconstruction methods, HIV-TRACE and Cluster Picker, using 1695 HIV-1 pol sequences obtained from 139 HIV-infected foreigners and 1556 Chinese natives in Guangzhou, China from 2008 to 2012. The geographic origin of the HIV-1 sequences was further determined by PastML while the factors associated with recent HIV-1 transmission were documented by logistic regression analysis.

RESULTS

HIV-1 genotypes that are prevalent in African and East Asian countries were identified in HIV-infected Chinese subjects and vice versa. In addition, more NRTI drug resistance mutations were found in HIV-infected foreigners than in native Chinese (p < 0.001). HIV-1 transmission between HIV-infected foreigners and native Chinese individuals was documented in 12.95% (18/139) of the HIV-infected foreigners. Furthermore, Asian (odds ratio [OR] = 3.45), male (OR = 16.88) and those with known HIV-1 infection routes (OR = 3.23) were more likely associated with recent HIV-1 transmission in China. The Chinese natives linked to recent HIV-1 transmission were more likely to be infected through men who have sex with men (OR = 3.05) or people who inject drugs (OR = 3.05), rather than by heterosexual transmission.

CONCLUSION

Our study demonstrates the impact of recent HIV-1 transmission between HIV-infected foreigners and Chinese natives on the HIV-1 epidemic in Guangzhou, China. Moreover, the results highlight the importance of phylogenetic analysis of HIV-1 surveillance data and the need for specific prevention strategies that target the immigrant population.

Undetectable viral load and HIV transmission dynamics on an individual and population level: where next in the global HIV response?

PURPOSE OF REVIEW

To examine recent literature on the efficacy and effectiveness of HIV treatment in preventing HIV transmission through sexual exposure, at both an individual and at a population level.

RECENT FINDINGS

Two recent studies on the individual-level efficacy of treatment as prevention (TasP) have added to the now conclusive evidence that HIV cannot be transmitted sexually when the virus is suppressed. However, four large cluster-randomized population-level trials on universal HIV testing and treatment in Africa have not delivered the expected impact in reducing HIV incidence at a population level. Two of these trials showed no differences in HIV incidence between the intervention and control arms, one demonstrated a nonsignificant lower incidence in the intervention arm, and the fourth trial found a reduction between the communities receiving a combination prevention package and the control arm, but no difference between the immediate treatment plus the prevention package and the control arm. Factors contributing to the disconnect between individual high-level efficacy and population-level effectiveness of TasP include undiagnosed infection, delays in linkage to care, challenges in retention and adherence to antiretroviral therapy (ART), time between ART initiation and viral suppression, and stigma and discrimination.

SUMMARY

Suppressive ART renders people living with HIV sexually noninfectious. However, epidemic control is unlikely to be achieved by TasP alone.

Porcine reproductive and respiratory syndrome virus dissemination across pig production systems in the United States

Porcine reproductive and respiratory syndrome virus (PRRSV) remains widespread in the North American pig population. Despite improvements in virus characterization, it is unclear whether PRRSV infections are a product of viral circulation within production systems (local) or across production systems (external). Here, we examined the local and external dissemination dynamics of PRRSV and the processes facilitating its spread in three production systems. Overall, PRRSV genetic diversity has declined since 2018, while phylodynamic results support frequent external transmission. We found that PRRSV dissemination predominantly occurred mostly through transmission between farms of different production companies for several months, especially from November until May, a timeframe already established as PRRSV season. Although local PRRSV dissemination occurred mainly through regular pig flow (from sow to nursery and then to finisher farms), an important flux of PRRSV dissemination also occurred in the opposite direction, from finisher to sow and nursery farms, highlighting the importance of downstream farms as sources of the virus. Our results also showed that farms with pig densities of 500 to 1,000 pig/km² and farms located at a range within 0.5 km and 0.7 km from major roads were more likely to be infected by PRRSV, whereas farms at an elevation of 41 to 61 meters and surrounded by denser vegetation were less likely to be infected, indicating their role as dissemination barriers. In conclusion, our results demonstrate that external dissemination was intense, and reinforce the importance of farm proximity on PRRSV spread. Thus, consideration of farm location, geographic characteristics and animal densities across production systems may help to forecast PRRSV collateral dissemination.

HIV incidence declines in a rural South African population: a G-imputation approach for inference

BACKGROUND

Ad hoc assumptions about the unobserved infection event, which is known only to occur between the latest-negative and earliest-positive test dates, can lead to biased HIV incidence rate estimates. Using a G-imputation approach, we infer the infection dates from covariate data to estimate the HIV incidence rate in a hyper-endemic South African setting.

METHODS

A large demographic surveillance system has annually tested a cohort of HIV-uninfected participants living in the KwaZulu-Natal province. Using this data, we estimated a cumulative baseline hazard function and the effects of time-dependent covariates on the interval censored infection dates. For each HIV-positive participant in the cohort, we derived a cumulative distribution function and sampled multiple infection dates conditional on the unique covariate values. We right censored the data at the imputed dates, calculated the annual HIV incidence rate per 100 person-years, and used Rubin's rules to obtain the 95% confidence intervals.

RESULTS

A total of 20,011 uninfected individuals with a repeat HIV test participated in the incidence cohort between 2005 and 2018. We observed 2,603 infections per 58,769 person-years of follow-up among women and 845 infections per 41,178 person-years of follow-up among men. Conditional on age and circumcision status (men only), the female HIV incidence rate declined by 25%, from 5.0 to 3.7 infections per 100 person-years between 2014 and 2018. During this period, the HIV incidence rate among men declined from 2.1 to 1.1 infections per 100 person-years-a reduction of 49%. We observed similar reductions in male and female HIV incidence conditional on condom-use, marital status, urban residential status, migration history, and the HIV prevalence in the surrounding community.

CONCLUSION

We have followed participants in one of the world's largest and longest running HIV cohorts to estimate long-term trends in the population-wide incidence of infection. Using a G-imputation approach, we present further evidence for HIV incidence rate declines in this hyper-endemic South African setting.

Phylogenetic and Demographic Characterization of Directed HIV-1 Transmission Using Deep Sequences from High-Risk and General Population Cohorts/Groups in Uganda

Across sub-Saharan Africa, key populations with elevated HIV-1 incidence and/or prevalence have been identified, but their contribution to disease spread remains unclear. We performed viral deep-sequence phylogenetic analyses to quantify transmission dynamics between the general population (GP), fisherfolk communities (FF), and women at high risk of infection and their clients (WHR) in central and southwestern Uganda. Between August 2014 and August 2017, 6185 HIV-1 positive individuals were enrolled in 3 GP and 10 FF communities, 3 WHR enrollment sites. A total of 2531 antiretroviral therapy (ART) naïve participants with plasma viral load >1000 copies/mL were deep-sequenced. One hundred and twenty-three transmission networks were reconstructed, including 105 phylogenetically highly supported source–recipient pairs. Only one pair involved a WHR and male participant, suggesting that improved population sampling is needed to assess empirically the role of WHR to the transmission dynamics. More transmissions were observed from the GP communities to FF communities than vice versa, with an estimated flow ratio of 1.56 (95% CrI 0.68–3.72), indicating that fishing communities on Lake Victoria are not a net source of transmission flow to neighboring communities further inland. Men contributed disproportionally to HIV-1 transmission flow regardless of age, suggesting that prevention efforts need to better aid men to engage with and stay in care.

The Impact of Human Mobility on Regional and Global Efforts to Control HIV Transmission

HIV prevention and control methods are implemented on different scales to reduce the spread of the virus amongst populations. However, despite such efforts, HIV continues to persist in populations with a global incidence rate of 1.8 million in 2017 alone. The introduction of new infections into susceptible regional populations promotes the spread of HIV, indicating a crucial need to study the impact of migration and mobility on regional and global efforts to prevent HIV transmission. Here we reviewed studies that assess the impact of human mobility on HIV transmission and spread. We found an important role for both travel and migration in driving the spread of HIV across regional and national borders. Combined, our results indicate that even in the presence of control and preventive efforts, if migration and travel are occurring, public health efforts will need to remain persistent to ensure that new infections do not grow into outbreaks.

Phylodynamic analysis of HIV-1 subtypes B, C and CRF 02_AG in Senegal

Surveillance of HIV epidemics in key populations and in developing countries is often challenging due to sparse, incomplete, or low-quality data. Analysis of HIV sequence data can provide an alternative source of information about epidemic history, population structure, and transmission patterns. To understand HIV-1 dynamics and transmission patterns in Senegal, we carried out model-based phylodynamic analyses using the structured-coalescent approach using HIV-1 sequence data from three different subgroups: reproductive aged males and females from the adult Senegalese population and men who have sex with other men (MSM). We fitted these phylodynamic analyses to time-scaled phylogenetic trees individually for subtypes C and CRF 02_AG, and for the combined data for subtypes B, C and CRF 02_AG. In general, the combined analysis showed a decreasing proportion of effective number of infections among all reproductive aged adults relative to MSM. However, we observed a nearly time-invariant distribution for subtype CRF 02_AG and an increasing trend for subtype C on the proportion of effective number of infections. The population attributable fraction also differed between analyses: subtype CRF 02_AG showed little contribution from MSM, while for subtype C and combined analyses this contribution was much higher. Despite observed differences, results suggested that the combination of high assortativity among MSM and the unmet HIV prevention and treatment needs represent a significant component of the HIV epidemic in Senegal.

A method for statistical analysis of repeated residential movements to link human mobility and HIV acquisition

We propose a method for analyzing repeated residential movements based on graphical loglinear models. This method allows an explicit representation of residential presence and absence patterns from several areas without defining mobility measures. We make use of our method to analyze data from one of the most comprehensive demographic surveillance sites in Africa that is characterized by high adult HIV prevalence, high levels of poverty and unemployment and frequent residential changes. Between 2004 and 2016, residential changes were recorded for 8,857 men over 35,500.01 person-years, and for 12,158 women over 57,945.35 person-years. These individuals were HIV negative at baseline. Over the study duration, there were a total of 806 HIV seroconversions in men, and 2,458 HIV seroconversions in women. Our method indicates that establishing a residence outside the rural study area is a strong predictor of HIV seroconversion in men (OR = 2.003, 95% CI = [1.718,2.332]), but not in women. Residing inside the rural study area in a single or in multiple locations is a less significant risk factor for HIV acquisition in both men and women compared to moving outside the rural study area.