Incidence rate estimation, periodic testing and the limitations of the mid-point imputation approach

Effect of population viral load on prospective HIV incidence in a hyperendemic rural African community

Monitoring HIV population viral load (PVL) has been advocated as an important means of inferring HIV transmission potential and predicting the future rate of new HIV infections (HIV incidence) in a particular community. However, the relationship between PVL measures and directly measured HIV incidence has not been quantified in any setting and, most importantly, in a hyperendemic sub-Saharan African setting. We assessed this relationship using one of Africa's largest population-based prospective population cohorts in rural KwaZulu-Natal, South Africa in which we followed 8732 HIV-uninfected participants between 2011 and 2015. Despite clear evidence of spatial clustering of high viral loads in some communities, our results demonstrate that PVL metrics derived from aggregation of viral load data only from the HIV-positive members of a particular community did not predict HIV incidence in this typical hyperendemic, rural African population. Only once we used modified PVL measures, which combined viral load information with the underlying spatial variation in the proportion of the population infected (HIV prevalence), did we find a consistently strong relationship with future risk of HIV acquisition. For example, every 1% increase in the overall proportion of a population having detectable virus (PDV _P ) was independently associated with a 6.3% increase in an individual's risk of HIV acquisition (P = 0.001). In hyperendemic African populations, these modified PVL indices could play a key role in targeting and monitoring interventions in the most vulnerable communities where the future rate of new HIV infections is likely to be highest.

Fecal Indicator Bacteria along Multiple Environmental Transmission Pathways (Water, Hands, Food, Soil, Flies) and Subsequent Child Diarrhea in Rural Bangladesh

Enteric pathogens can be transmitted through multiple environmental pathways, yet little is known about the relative contribution of each pathway to diarrhea risk among children. We aimed to identify fecal transmission pathways in the household environment associated with prospectively measured child diarrhea in rural Bangladesh. We measured the presence and levels of Escherichia coli in tube wells, stored drinking water, pond water, child hand rinses, courtyard soil, flies, and food in 1843 households. Gastrointestinal symptoms among children ages 0-60 months were recorded concurrently at the time of environmental sample collection and again a median of 6 days later. Incident diarrhea (3 or more loose stools in a 24-h period) was positively associated with the concentration of E. coli on child hands measured on the first visit (incidence rate ratio [IRR] = 1.23, 95% CI 1.06, 1.43 for a log₁₀ increase), while other pathways were not associated. In cross-sectional analysis, there were no associations between concurrently measured environmental contamination and diarrhea. Our findings suggest higher levels of E. coli on child hands are strongly associated with subsequent diarrheal illness rates among children in rural Bangladesh.

Relational concurrency, stages of infection, and the evolution of HIV set point viral load

HIV viral load (VL) predicts both transmission potential and rate of disease progression. For reasons that are still not fully understood, the set point viral load (SPVL) established after acute infection varies across individuals and populations. Previous studies have suggested that population mean SPVL (MSPVL) has evolved near an optimum that reflects a trade-off between transmissibility and host survival. Sexual network structures affect rates of potential exposure during different within-host phases of infection marked by different transmission probabilities, and thus affect the number and timing of transmission events. These structures include relational concurrency, which has been argued to explain key differences in HIV burden across populations. We hypothesize that concurrency will alter the fitness landscape for SPVL in ways that differ from other network features whose impacts accrue at other times during infection. To quantitatively test this hypothesis, we developed a dynamic, stochastic, data-driven network model of HIV transmission, and evolution to assess the impact of key sexual network phenomena on MSPVL evolution. Experiments were repeated in sensitivity runs that made different assumptions about transmissibility during acute infection, SPVL heritability, and the functional form of the relationship between VL and transmissibility. For our main transmission model, scenarios yielded MSPVLs ranging from 4.4 to 4.75 log10 copies/ml, covering much of the observed empirical range. MSPVL evolved to be higher in populations with high concurrency and shorter relational durations, with values varying over a clinically significant range. In linear regression analyses on these and other predictors, main effects were significant (P < 0.05), as were interaction terms, indicating that effects are interdependent. We also noted a strong correlation between two key emergent properties measured at the end of the simulations-MSPVL and HIV prevalence-most clearly for phenomena that affect transmission networks early in infection. Controlling for prevalence, high concurrency yielded higher MSPVL than other network phenomena. Interestingly, we observed lower prevalence in runs in which SPVL heritability was zero, indicating the potential for viral evolution to exacerbate disease burden over time. Future efforts to understand empirical variation in MSPVL should consider local HIV burden and basic sexual behavioral and network structure.

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

Despite increasing access to antiretrovirals, HIV incidence in rural KwaZulu-Natal remains among the highest ever reported in Africa. While many epidemiological factors have been invoked to explain such high incidence, widespread human mobility and viral movement suggest that transmission between communities may be a major source of new infections. High cross-community transmission rates call into question how effective increasing the coverage of antiretroviral therapy locally will be at preventing new infections, especially if many new cases arise from external introductions. To help address this question, we use a phylodynamic model to reconstruct epidemic dynamics and estimate the relative contribution of local transmission versus external introductions to overall incidence in KwaZulu-Natal from HIV-1 phylogenies. By comparing our results with population-based surveillance data, we show that we can reliably estimate incidence from viral phylogenies once viral movement in and out of the local population is accounted for. Our analysis reveals that early epidemic dynamics were largely driven by external introductions. More recently, we estimate that 35 per cent (95% confidence interval: 20-60%) of new infections arise from external introductions. These results highlight the growing need to consider larger-scale regional transmission dynamics when designing and testing prevention strategies.

High percentage of undiagnosed HIV cases within a hyperendemic South African community: a population-based study

BACKGROUND

Undiagnosed HIV infections could undermine efforts to reverse the global AIDS epidemic by 2030. In this study, we estimated the percentage of HIV-positive persons who remain undiagnosed within a hyperendemic South African community.

METHODS

The data come from a population-based surveillance system located in the Umkhanyakude district of the northern KwaZulu-Natal province, South Africa. We annually tested 38 661 adults for HIV between 2005 and 2016. Using the HIV-positive test results of 12 039 (31%) participants, we then back-calculated the incidence of infection and derived the number of undiagnosed cases from this result.

RESULTS

The percentage of undiagnosed HIV cases decreased from 29.3% in 2005 to 15.8% in 2011. During this period, however, approximately 50% of the participants refused to test for HIV, which lengthened the average time from infection to diagnosis. Consequently, the percentage of undiagnosed HIV cases reversed direction and steadily increased from 16.1% to 18.9% over the 2012-2016 period.

CONCLUSIONS

Results from this hyperendemic South African setting show that the HIV testing rate is low, with long infection times, and an unsatisfactorily high percentage of undiagnosed cases. A high level of repeat HIV testing is needed to minimise the time from infection to diagnosis if the global AIDS epidemic is to be reversed within the next two decades.