Strong influence of behavioral dynamics on the ability of testing and treating HIV to stop transmission

Transitions in sexual behaviour among gay, bisexual, and other men who have sex with men in England: Data from a prospective study

The effectiveness of population-level intervention for HIV elimination is influenced by individual-level variation in sexual behaviour. We assess within-person changes in the frequency of condomless anal sex with two or more partners (CLS2+), estimate the transition probabilities and examine the predictors of transitions among a prospective cohort of HIV-negative gay, bisexual, and other men who have sex with men (GBMSM). Participants were recruited through one of three sexual health clinics in London and Brighton (July 2013 to April 2016) and self-completed a baseline paper questionnaire in the clinic. During follow-up, they were invited to complete four-monthly questionnaires twice a year and subsequent annual online questionnaires once a year (March 2015 to March 2018). We used Markov chain models to estimate transition probabilities from 'higher-risk' (CLS2+) to 'lower-risk' (no CLS2+) and vice versa, and to assess factors associated with transitions between different sexual risk levels. Among 1,162 men enrolled in the study, 622 (53.5%) completed at least one online questionnaire. Higher-risk behaviour was reported in 376/622 (60.4%) men during online follow-up. Overall, 1,665/3,277 (37.5%) baseline and follow-up questionnaires reported higher-risk behaviour. More than 60% of men (376/622) reported higher-risk behaviour at least one period during the follow-up, while 39.5% of men (246/622) never reported CLS2+ during the follow-up. In the next four months, the estimated probability of continuing higher-risk behaviour among men who reported higher-risk behaviour was 78%. Calendar time, recent HIV tests, PrEP and PEP use were the predictors of staying in higher-risk behaviour, while less stable housing status was associated with switching to lower-risk behaviour. Among men who reported lower-risk behaviour, the probability of engaging in the same behaviour was 88%. Recent HIV tests, PrEP and PEP use, recreational drugs, chemsex-associated drug and injection drugs, and bacterial STIs diagnosis were the predictors of switching to higher-risk behaviour. Our results indicate that at any one point in time, the majority of GBMSM are at low risk for HIV acquisition, although many experience short periods in which they are at higher risk. Markers of transitions can be utilized to identify which GBMSM are likely to increase or decrease their risk, thus helping the timing of HIV prevention interventions.

Risk heterogeneity in compartmental HIV transmission models of ART as prevention in Sub-Saharan Africa: A scoping review

BACKGROUND

Transmission models provide complementary evidence to clinical trials about the potential population-level incidence reduction attributable to ART (ART prevention impact). Different modelling assumptions about risk heterogeneity may influence projected ART prevention impacts. We sought to review representations of risk heterogeneity in compartmental HIV transmission models applied to project ART prevention impacts in Sub-Saharan Africa.

METHODS

We systematically reviewed studies published before January 2020 that used non-linear compartmental models of sexual HIV transmission to simulate ART prevention impacts in Sub-Saharan Africa. We summarized data on model structure/assumptions (factors) related to risk and intervention heterogeneity, and explored multivariate ecological associations of ART prevention impacts with modelled factors.

RESULTS

Of 1384 search hits, 94 studies were included. 64 studies considered sexual activity stratification and 39 modelled at least one key population. 21 studies modelled faster/slower ART cascade transitions (HIV diagnosis, ART initiation, or cessation) by risk group, including 8 with faster and 4 with slower cascade transitions among key populations versus the wider population. In ecological analysis of 125 scenarios from 40 studies (subset without combination intervention), scenarios with risk heterogeneity that included turnover of higher risk groups were associated with smaller ART prevention benefits. Modelled differences in ART cascade across risk groups also influenced the projected ART benefits, including: ART prioritized to key populations was associated with larger ART prevention benefits. Of note, zero of these 125 scenarios considered lower ART coverage among key populations.

CONCLUSION

Among compartmental transmission models applied to project ART prevention impacts in Sub-Saharan Africa, representations of risk heterogeneity and projected impacts varied considerably. Inclusion/exclusion of risk heterogeneity with turnover, and intervention heterogeneity across risk groups could influence the projected impacts of ART scale-up. These findings highlight a need to capture risk heterogeneity with turnover and cascade heterogeneity when projecting ART prevention impacts.

Temporal Variation in One-Time Partnership Rates Among Young Men Who Have Sex With Men and Transgender Women

BACKGROUND

Volatility in sexual contact rates has been recognized as an important factor influencing HIV transmission dynamics. One-time partnerships may be particularly important given the potential to quickly accumulate large number of contacts. Yet, empirical data documenting individual variation in contact rates remain rare. This study provides much needed data on temporal variation in one-time partners to better understand behavioral dynamics and improve the accuracy of transmission models.

METHODS

Data for this study were obtained from a longitudinal cohort study of young men who have sex with men and transgender women in Chicago. Participants provided sexual network data every 6 months for 2 years. A series of random effects models examined variation in one-time partnership rates and disaggregated within and between associations of exposure variables. Exposure variables included prior number of one-time partners, number of casual partners, and having a main partner.

RESULTS

Results indicated substantial between-person and within-person variation in one-time partners. Casual partnerships were positively associated and main partnerships negatively associated with one-time partnership rates. There remained a small positive association between prior one-time partnerships and the current number of one-time partnerships.

CONCLUSIONS

Despite the preponderance of a low number of one-time partners, substantial variation in one-time partnership rates exists among young men who have sex with men and transgender women. Accordingly, focusing on high contact rate individuals alone may be insufficient to identify periods of highest risk. Future studies should use these estimates to more accurately model how volatility impacts HIV transmission and better understand how this variation influences intervention effectiveness.

Modelling the impact of tailored behavioural interventions on chlamydia transmission

Behavioural interventions tailored to psychological characteristics of an individual can effectively achieve risk-reducing behaviour. The impact of tailored interventions on population-level chlamydia prevalence is unknown. We aimed to assess the impact on overall chlamydia prevalence five years after the introduction of an intervention aimed at increasing self-efficacy, social norms, attitudes and intentions towards condom use (i.e., condom intervention), and an intervention aimed at increasing health goals and decreasing impulsiveness (i.e., impulsiveness intervention). A pair model, informed by longitudinal psychological and behavioural data of young heterosexuals visiting sexual health centers, with susceptible-infected-susceptible structure was developed. The intervention effect was defined as an increased proportion of each subgroup moving to the desired subgroup (i.e., lower risk subgroup). Interventions tailored to subgroup-specific characteristics, assuming differential intervention effects in each subgroup, more effectively reduced overall chlamydia prevalence compared to non-tailored interventions. The most effective intervention was the tailored condom intervention, which was assumed to result in a relative reduction in chlamydia prevalence of 18% versus 12% in the non-tailored scenario. Thus, it is important to assess multiple psychological and behavioural characteristics of individuals. Tailored interventions may be more successful in achieving risk-reducing behaviour, and consequently, reduce chlamydia prevalence more effectively.

Clusters of Sexual Behavior in Human Immunodeficiency Virus-positive Men Who Have Sex With Men Reveal Highly Dissimilar Time Trends

BACKGROUND

Separately addressing specific groups of people who share patterns of behavioral change might increase the impact of behavioral interventions to prevent transmission of sexually transmitted infections. We propose a method based on machine learning to assist the identification of such groups among men who have sex with men (MSM).

METHODS

By means of unsupervised learning, we inferred "behavioral clusters" based on the recognition of similarities and differences in longitudinal patterns of condomless anal intercourse with nonsteady partners (nsCAI) in the HIV Cohort Study over the last 18 years. We then used supervised learning to investigate whether sociodemographic variables could predict cluster membership.

RESULTS

We identified 4 behavioral clusters. The largest behavioral cluster (cluster 1) contained 53% of the study population and displayed the most stable behavior. Cluster 3 (17% of the study population) displayed consistently increasing nsCAI. Sociodemographic variables were predictive for both of these clusters. The other 2 clusters displayed more drastic changes: nsCAI frequency in cluster 2 (20% of the study population) was initially similar to that in cluster 3 but accelerated in 2010. Cluster 4 (10% of the study population) had significantly lower estimates of nsCAI than all other clusters until 2017, when it increased drastically, reaching 85% by the end of the study period.

CONCLUSIONS

We identified highly dissimilar behavioral patterns across behavioral clusters, including drastic, atypical changes. The patterns suggest that the overall increase in the frequency of nsCAI is largely attributable to 2 clusters, accounting for a third of the population.

Contribution of high risk groups' unmet needs may be underestimated in epidemic models without risk turnover: A mechanistic modelling analysis

Background

Epidemic models of sexually transmitted infections (STIs) are often used to characterize the contribution of risk groups to overall transmission by projecting the transmission population attributable fraction (tPAF) of unmet prevention and treatment needs within risk groups. However, evidence suggests that STI risk is dynamic over an individual’s sexual life course, which manifests as turnover between risk groups. We sought to examine the mechanisms by which turnover influences modelled projections of the tPAF of high risk groups.

Methods

We developed a unifying, data-guided framework to simulate risk group turnover in deterministic, compartmental transmission models. We applied the framework to an illustrative model of an STI and examined the mechanisms by which risk group turnover influenced equilibrium prevalence across risk groups. We then fit a model with and without turnover to the same risk-stratified STI prevalence targets and compared the inferred level of risk heterogeneity and tPAF of the highest risk group projected by the two models.

Results

The influence of turnover on group-specific prevalence was mediated by three main phenomena: movement of previously high risk individuals with the infection into lower risk groups; changes to herd effect in the highest risk group; and changes in the number of partnerships where transmission can occur. Faster turnover led to a smaller ratio of STI prevalence between the highest and lowest risk groups. Compared to the fitted model without turnover, the fitted model with turnover inferred greater risk heterogeneity and consistently projected a larger tPAF of the highest risk group over time.

Implications

If turnover is not captured in epidemic models, the projected contribution of high risk groups, and thus, the potential impact of prioritizing interventions to address their needs, could be underestimated. To aid the next generation of tPAF models, data collection efforts to parameterize risk group turnover should be prioritized.

•

A new framework for parameterizing turnover in risk groups is developed.

•

Mechanisms by which turnover influences sexually transmitted infection (STI), prevalence in risk groups are examined.

•

Turnover reduces the ratio of equilibrium STI prevalence in high vs low risk groups.

•

Inferred risk heterogeneity is higher when fitting transmission models with turnover.

•

Ignoring turnover in risk could underestimate the transmission population attributable fraction (tPAF), of high risk groups to the overall epidemic.

A novel Bayesian approach to predicting reductions in HIV incidence following increased testing interventions among gay, bisexual and other men who have sex with men in Vancouver, Canada

Increasing HIV testing rates among high-risk groups should lead to increased numbers of cases being detected. Coupled with effective treatment and behavioural change among individuals with detected infection, increased testing should also reduce onward incidence of HIV in the population. However, it can be difficult to predict the strengths of these effects and thus the overall impact of testing. We construct a mathematical model of an ongoing HIV epidemic in a population of gay, bisexual and other men who have sex with men. The model incorporates different levels of infection risk, testing habits and awareness of HIV status among members of the population. We introduce a novel Bayesian analysis that is able to incorporate potentially unreliable sexual health survey data along with firm clinical diagnosis data. We parameterize the model using survey and diagnostic data drawn from a population of men in Vancouver, Canada. We predict that increasing testing frequency will yield a small-scale but long-term impact on the epidemic in terms of new infections averted, as well as a large short-term impact on numbers of detected cases. These effects are predicted to occur even when a testing intervention is short-lived. We show that a short-lived but intensive testing campaign can potentially produce many of the same benefits as a campaign that is less intensive but of longer duration.

Impact of sexual trajectories of men who have sex with men on the reduction in HIV transmission by pre-exposure prophylaxis

Changes in sexual risk behavior over the life course in men who have sex with men (MSM) can influence population-level intervention efficacy. Our objective was to investigate the impact of incorporating sexual trajectories describing long-term changes in risk levels on the reduction in HIV prevalence by pre-exposure prophylaxis (PrEP) among MSM. Based on the Amsterdam Cohort Study data, we developed two models of HIV transmission in a population stratified by sexual behavior. In the first model, individuals were stratified into low, medium and high risk levels and did not change their risk levels. The second model had the same stratification but incorporated additionally three types of sexual behavior trajectories. The models assumed universal antiretroviral treatment of HIV⁺ MSM, and PrEP use by high risk HIV^- MSM. We computed the relative reduction in HIV prevalence in both models for annual PrEP uptakes of 10% to 80% at different time points after PrEP introduction. We then investigated the impact of sexual trajectories on the effectiveness of PrEP intervention. The impact of sexual trajectories on the overall prevalence and prevalence in individuals at low, medium and high risk levels varied with PrEP uptake and time after PrEP introduction. Compared to the model without sexual trajectories, the model with trajectories predicted a higher impact of PrEP on the overall prevalence, and on the prevalence among the medium and high risk individuals. In low risk individuals, there was more reduction in prevalence during the first 15 years of PrEP intervention if sexual trajectories were not incorporated in the model. After that point, at low risk level there was more reduction in the model with trajectories. In conclusion, our study predicts that sexual trajectories increase the estimated impact of PrEP on reducing HIV prevalence when compared to a population where risk levels do not change.

Numerical optimal control for HIV prevention with dynamic budget allocation

This article is about numerical control of HIV propagation. The contribution of the article is threefold: first, a novel model of HIV propagation is proposed; second, the methods from numerical optimal control are successfully applied to the developed model to compute optimal control profiles; finally, the computed results are applied to the real problem yielding important and practically relevant results.

Systematic evaluation of the population-level effects of alternative treatment strategies on the basic reproduction number

An approach to estimate the influence of the treatment-type controls on the basic reproduction number, R₀, is proposed and elaborated. The presented approach allows one to estimate the effect of a given treatment strategy or to compare a number of different treatment strategies on the basic reproduction number. All our results are valid for sufficiently small values of the control. However, in many cases it is possible to extend this analysis to larger values of the control as was illustrated by examples.

Elimination prospects of the Dutch HIV epidemic among men who have sex with men in the era of preexposure prophylaxis

Objective:

Preexposure prophylaxis (PrEP) is a promising intervention to help end the HIV epidemic among men who have sex with men (MSM) in the Netherlands. We aimed to assess the impact of PrEP on HIV prevalence in this population and to determine the levels of PrEP coverage necessary for HIV elimination.

Design and methods:

We developed a mathematical model of HIV transmission in a population stratified by sexual risk behavior with universal antiretroviral treatment (ART) and daily PrEP use depending on an individual's risk behavior. We computed the effective reproduction number, HIV prevalence, ART and PrEP coverage for increasing ART and PrEP uptake levels, and examined how these were affected by PrEP effectiveness and duration of PrEP use.

Results:

At current levels of ART coverage of 80%, PrEP effectiveness of 86% and PrEP duration of 5 years, HIV elimination required 82% PrEP coverage in the highest risk group (12 000 MSM with more than 18 partners per year). If ART coverage increased by 9%, the elimination threshold was at 70% PrEP coverage. For shorter PrEP duration and lower effectiveness elimination prospects were less favorable. For the same number of PrEP users distributed among two groups with highest risk behavior, prevalence dropped from the current 8 to 4.6%.

Conclusion:

PrEP for HIV prevention among MSM could, in principle, eliminate HIV from this population in the Netherlands. The highest impact of PrEP on prevalence was predicted when ART and PrEP coverage increased simultaneously and PrEP was used by the highest risk individuals.

Sensitivity of joint contagiousness and susceptibility-based dynamic optimal control strategies for HIV prevention

Predicting the population-level effects of an infectious disease intervention that incorporate multiple modes of intervention is complicated by the joint non-linear dynamics of both infection transmission and the intervention itself. In this paper, we consider the sensitivity of Dynamic Optimal Control Profiles (DOCPs) for the optimal joint investment in both a contagiousness and susceptibility-based control of HIV to bio-behavioral, economic, and programmatic assumptions. The DOCP is calculated using recently developed numerical algorithms that allow controls to be represented by a set of piecewise constant functions that maintain a constant yearly budget. Our transmission model assumes multiple stages of HIV infection corresponding to acute and chronic infection and both within- and between-individual behavioral heterogeneity. We parameterize a baseline scenario from a longitudinal study of sexual behavior in MSM and consider sensitivity of the DOCPs to deviations from that baseline scenario. In the baseline scenario, the primary determinant of the dominant control were programmatic factors, regardless of budget. In sensitivity analyses, the qualitative aspects of the optimal control policy were often robust to significant deviation in assumptions regarding transmission dynamics. In addition, we found several conditions in which long-term joint investment in both interventions was optimal. Our results suggest that modeling in the service of decision support for intervention design can improve population-level effects of a limited set of economic resources. We found that economic and programmatic factors were as important as the inherent transmission dynamics in determining population-level intervention effects. Given our finding that the DOCPs were robust to alternative biological and behavioral assumptions it may be possible to identify DOCPs even when the data are not sufficient to identify a transmission model.

Modelling the dynamics of population viral load measures under HIV treatment as prevention

In 2011 the Centers for Disease Control and Prevention (CDC) published guidelines for the use of population viral load (PVL), community viral load (CVL) and monitored viral load (MVL), defined as the average viral load (VL) of all HIV infected individuals in a population, of all diagnosed individuals, and of all individuals on antiretroviral treatment (ART), respectively. Since then, CVL has been used to assess the effectiveness of ART on HIV transmission and as a proxy for HIV incidence. The first objective of this study was to investigate how aggregate VL measures change with the HIV epidemic phase and the drivers behind these changes using a mathematical transmission model. Secondly, we aimed to give some insight into how well CVL correlates with HIV incidence during the course of the epidemic and roll out of ART. We developed a compartmental model for disease progression and HIV transmission with disease stages that differ in viral loads for epidemiological scenarios relevant to a concentrated epidemic in a population of men who have sex with men (MSM) in Western Europe (WE) and to a generalized epidemic in a heterosexual population in Sub-Saharan Africa (SSA). The model predicts that PVL and CVL change with the epidemic phase, while MVL stays constant. These dynamics are linked to the dynamics of infected subgroups (undiagnosed, diagnosed untreated and treated) in different disease stages (primary, chronic and AIDS). In particular, CVL decreases through all epidemic stages: before ART, since chronic population builds up faster than AIDS population and after ART, due to the build-up of treated population with low VL. The trends in CVL and incidence can be both opposing and coinciding depending on the epidemic phase. Before ART is scaled up to sufficiently high levels, incidence increases while CVL decreases. After this point, CVL is a useful indicator of changes in HIV incidence. The model predicts that during the ART scale-up HIV transmission is driven by undiagnosed and diagnosed untreated individuals, and that new infections decline due to the increase in the number of treated. Although CVL is not able to capture the contribution of undiagnosed population to HIV transmission, it declines due to the increase of people on ART too. In the scenarios described by our model, the present epidemic phase corresponds to declining trends in CVL and incidence.

Risk stratification in compartmental epidemic models: Where to draw the line?

Economic evaluations of infectious disease control interventions frequently use dynamic compartmental epidemic models. Such models capture heterogeneity in risk of infection by stratifying the population into discrete risk groups, thus approximating what is typically continuous variation in risk. An important open question is whether and how different risk stratification choices influence model predictions of intervention effects. We develop equivalent Susceptible-Infected-Susceptible (SIS) dynamic transmission models: an unstratified model, a model stratified into a high-risk and low-risk group, and a model with an arbitrary number of risk groups. Absent intervention, the models produce the same overall prevalence of infected individuals in steady state. We consider an intervention that either reduces the contact rate or increases the disease clearance rate. We develop analytical and numerical results characterizing the models and the effects of the intervention. We find that there exist multiple feasible choices of risk stratification, contact distribution, and within- and between-group contact rates for models that stratify risk. We show analytically and empirically that these choices can generate different estimates of intervention effectiveness, and that these differences can be significant enough to alter conclusions from cost-effectiveness analyses and change policy recommendations. We conclude that the choice of how to discretize risk in compartmental epidemic models can influence predicted effectiveness of interventions. Therefore, analysts should examine multiple alternatives and report the range of results.

A network intervention that locates and intervenes with recently HIV-infected persons: The Transmission Reduction Intervention Project (TRIP)

Early treatment, soon after infection, reduces HIV transmissions and benefits patients. The Transmission Reduction Intervention Project (TRIP) evaluated a network intervention to detect individuals recently infected (in the past 6 months). TRIP was conducted in Greece (2013-2015) and focused on drug injector networks. Based on HIV status, testing history, and the results of an assay to detect recent infections, TRIP classified drug injector "Seeds" into groups: Recent Seeds (RS), and Control Seeds with Long-term HIV infection (LCS). The network members of RS and LCS were traced for two steps. The analysis included 23 RS, 171 network members of the RS, 19 LCS, and 65 network members of the LCS. The per-seed number of recents detected in the network of RS was 5 times the number in the network of LCS (Ratio RS vs. LCS: 5.23; 95% Confidence Interval (CI): 1.54-27.61). The proportion of recents among HIV positives in the network of RS (27%) was approximately 3 times (Ratio RS vs. LCS: 3.30; 95% CI: 1.04-10.43) that in the network of LCS (8%). Strategic network tracing that starts with recently infected persons could support public health efforts to find and treat people early in their HIV infection.

Impact of Heterogeneity in Sexual Behavior on Effectiveness in Reducing HIV Transmission with Test-and-Treat Strategy

The WHO’s early-release guideline for antiretroviral treatment (ART) of HIV infection based on a recent trial conducted in 34 countries recommends starting treatment immediately upon an HIV diagnosis. Therefore, the test-and-treat strategy may become more widely used in an effort to scale up HIV treatment and curb further transmission. Here we examine behavioural determinants of HIV transmission and how heterogeneity in sexual behaviour influences the outcomes of this strategy. Using a deterministic model, we perform a systematic investigation into the effects of various mixing patterns in a population of men who have sex with men (MSM), stratified by partner change rates, on the elimination threshold and endemic HIV prevalence. We find that both the level of overdispersion in the distribution of the number of sexual partners and mixing between population subgroups have a large influence on endemic prevalence before introduction of ART and on possible long term effectiveness of ART. Increasing heterogeneity in risk behavior may lead to lower endemic prevalence levels, but requires higher coverage levels of ART for elimination. Elimination is only feasible for populations with a rather low degree of assortativeness of mixing and requires treatment coverage of almost 80% if rates of testing and treatment uptake by all population subgroups are equal. In this case, for fully assortative mixing and 80% coverage endemic prevalence is reduced by 57%. In the presence of heterogeneity in ART uptake, elimination is easier to achieve when the subpopulation with highest risk behavior is tested and treated more often than the rest of the population, and vice versa when it is less. The developed framework can be used to extract information on behavioral heterogeneity from existing data which is otherwise hard to determine from population surveys.

HIV is endemic in populations of MSM in Western countries. As ART reduces transmission risk, increased testing and treatment rates are expected to lower HIV incidence. However, concerns are that in MSM populations changing risk behavior may counteract the impact of ART on transmission. Using a mathematical model, we investigated how heterogeneity in sexual behavior influences the possible effects of a test-and-treat strategy on HIV prevalence and in particular the prospects of eliminating HIV from these populations. We demonstrated that behavioral heterogeneity plays an important role in determining the impact of ART on reducing HIV transmission. Knowledge of behavioral heterogeneity is key in setting intervention goals in populations of MSM.

Contact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants' attitudes

BACKGROUND

Studies measuring contact networks have helped to improve our understanding of infectious disease transmission. However, several methodological issues are still unresolved, such as which method of contact measurement is the most valid. Further, complete network analysis requires data from most, ideally all, members of a network and, to achieve this, acceptance of the measurement method. We aimed at investigating measurement error by comparing two methods of contact measurement - paper diaries vs. wearable proximity sensors - that were applied concurrently to the same population, and we measured acceptability.

METHODS

We investigated the contact network of one day of an epidemiology conference in September 2014. Seventy-six participants wore proximity sensors throughout the day while concurrently recording their contacts with other study participants in a paper-diary; they also reported on method acceptability.

RESULTS

There were 329 contact reports in the paper diaries, corresponding to 199 contacts, of which 130 were noted by both parties. The sensors recorded 316 contacts, which would have resulted in 632 contact reports if there had been perfect concordance in recording. We estimated the probabilities that a contact was reported in a diary as: P = 72 % for <5 min contact duration (significantly lower than the following, p < 0.05), P = 86 % for 5-15 min, P = 89 % for 15-60 min, and P = 94 % for >60 min. The sets of sensor-measured and self-reported contacts had a large intersection, but neither was a subset of the other. Participants' aggregated contact duration was mostly substantially longer in the diary data than in the sensor data. Twenty percent of respondents (>1 reported contact) stated that filling in the diary was too much work, 25 % of respondents reported difficulties in remembering contacts, and 93 % were comfortable having their conference contacts measured by sensors.

CONCLUSION

Reporting and recording were not complete; reporting was particularly incomplete for contacts <5 min. The types of contact that both methods are capable of detecting are partly different. Participants appear to have overestimated the duration of their contacts. Conducting a study with diaries or wearable sensors was acceptable to and mostly easily done by participants. Both methods can be applied meaningfully if their specific limitations are considered and incompleteness is accounted for.

Contact diaries versus wearable proximity sensors in measuring contact patterns at a conference: method comparison and participants' attitudes

Background

Studies measuring contact networks have helped to improve our understanding of infectious disease transmission. However, several methodological issues are still unresolved, such as which method of contact measurement is the most valid. Further, complete network analysis requires data from most, ideally all, members of a network and, to achieve this, acceptance of the measurement method. We aimed at investigating measurement error by comparing two methods of contact measurement – paper diaries vs. wearable proximity sensors – that were applied concurrently to the same population, and we measured acceptability.

Methods

We investigated the contact network of one day of an epidemiology conference in September 2014. Seventy-six participants wore proximity sensors throughout the day while concurrently recording their contacts with other study participants in a paper-diary; they also reported on method acceptability.

Results

There were 329 contact reports in the paper diaries, corresponding to 199 contacts, of which 130 were noted by both parties. The sensors recorded 316 contacts, which would have resulted in 632 contact reports if there had been perfect concordance in recording. We estimated the probabilities that a contact was reported in a diary as: P = 72 % for <5 min contact duration (significantly lower than the following, p < 0.05), P = 86 % for 5-15 min, P = 89 % for 15-60 min, and P = 94 % for >60 min. The sets of sensor-measured and self-reported contacts had a large intersection, but neither was a subset of the other. Participants’ aggregated contact duration was mostly substantially longer in the diary data than in the sensor data. Twenty percent of respondents (>1 reported contact) stated that filling in the diary was too much work, 25 % of respondents reported difficulties in remembering contacts, and 93 % were comfortable having their conference contacts measured by sensors.

Conclusion

Reporting and recording were not complete; reporting was particularly incomplete for contacts <5 min. The types of contact that both methods are capable of detecting are partly different. Participants appear to have overestimated the duration of their contacts. Conducting a study with diaries or wearable sensors was acceptable to and mostly easily done by participants. Both methods can be applied meaningfully if their specific limitations are considered and incompleteness is accounted for.

Electronic supplementary material

The online version of this article (doi:10.1186/s12879-016-1676-y) contains supplementary material, which is available to authorized users.