Induction of social contagion for diverse outcomes in structured experiments in isolated villages.

Certain people occupy topological positions within social networks that enhance their effectiveness at inducing spillovers. We mapped face-to-face networks among 24,702 people in 176 isolated villages in Honduras and randomly assigned villages to targeting methods, varying the fraction of households receiving a 22-month health education package and the method by which households were chosen (randomly versus using the friendship-nomination algorithm). We assessed 117 diverse knowledge, attitude, and practice outcomes. Friendship-nomination targeting reduced the number of households needed to attain specified levels of village-wide uptake. Knowledge spread more readily than behavior, and spillovers extended to two degrees of separation. Outcomes that were intrinsically easier to adopt also manifested greater spillovers. Network targeting using friendship nomination effectively promotes population-wide improvements in welfare through social contagion.

A Prospective Sociocentric Study of 2 Entire Traditional Korean Villages: The Korean Social Life, Health, and Aging Project (KSHAP).

The Korean Social Life, Health, and Aging Project (KSHAP) was a multidisciplinary prospective study conducted in South Korea that measured various health biomarkers from blood, hair, and brain magnetic resonance imaging, and we examined their associations with sociocentric (global) social network data of older adults in 2 entire villages (or cohorts). Cohort K included participants aged 60 years or older, and cohort L included participants aged 65 years or older. We performed a baseline survey involving 814 of the 860 individuals (94.7% response rate) in cohort K in 2012 and 947 of the 1,043 individuals (90.8% response rate) in cohort L in 2017. We gathered longitudinal data for 5 waves in cohort K from 2011 to 2019 and 2 waves in cohort L from 2017 to 2022. Here, we describe for the first time the follow-up design of the KSHAP, the changes in social networks, and various biomarkers over a number of years. The data for cohort K are publicly available via the Korean Social Science Data Archive as well as the project website, and the data for cohort L will be shared soon.

Emergence and collapse of reciprocity in semiautomatic driving coordination experiments with humans.

Forms of both simple and complex machine intelligence are increasingly acting within human groups in order to affect collective outcomes. Considering the nature of collective action problems, however, such involvement could paradoxically and unintentionally suppress existing beneficial social norms in humans, such as those involving cooperation. Here, we test theoretical predictions about such an effect using a unique cyber-physical lab experiment where online participants (N = 300 in 150 dyads) drive robotic vehicles remotely in a coordination game. We show that autobraking assistance increases human altruism, such as giving way to others, and that communication helps people to make mutual concessions. On the other hand, autosteering assistance completely inhibits the emergence of reciprocity between people in favor of self-interest maximization. The negative social repercussions persist even after the assistance system is deactivated. Furthermore, adding communication capabilities does not relieve this inhibition of reciprocity because people rarely communicate in the presence of autosteering assistance. Our findings suggest that active safety assistance (a form of simple AI support) can alter the dynamics of social coordination between people, including by affecting the trade-off between individual safety and social reciprocity. The difference between autobraking and autosteering assistance appears to relate to whether the assistive technology supports or replaces human agency in social coordination dilemmas. Humans have developed norms of reciprocity to address collective challenges, but such tacit understandings could break down in situations where machine intelligence is involved in human decision-making without having any normative commitments.

Emergency communications after earthquake reveal social network backbone of important ties.

Social networks provide a basis for collective resilience to disasters. Combining the quasi-experimental context of a major earthquake in Ya'an, China, with anonymized mobile telecommunications records regarding 91,839 Ya'an residents, we use initial bursts of postdisaster communications (e.g. choice of alter, order of calls, and latency) to reveal the "important ties" that form the social network backbone. We find that only 26.8% of important ties activated during the earthquake were the strongest ties during normal times. Many important ties were hitherto latent and weak, only to become persistent and strong after the earthquake. We show that which ties activated during a sudden disaster are best predicted by the interaction of embeddedness and tie strength. Moreover, a backbone of important ties alone (without the inclusion of weak ties ordinarily seen as important to bridge communities) is sufficient to generate a hierarchical structure of social networks that connect a disaster zone's disparate communities.

Clinically relevant antibiotic resistance genes are linked to a limited set of taxa within gut microbiome worldwide.

The acquisition of antimicrobial resistance (AR) genes has rendered important pathogens nearly or fully unresponsive to antibiotics. It has been suggested that pathogens acquire AR traits from the gut microbiota, which collectively serve as a global reservoir for AR genes conferring resistance to all classes of antibiotics. However, only a subset of AR genes confers resistance to clinically relevant antibiotics, and, although these AR gene profiles are well-characterized for common pathogens, less is known about their taxonomic associations and transfer potential within diverse members of the gut microbiota. We examined a collection of 14,850 human metagenomes and 1666 environmental metagenomes from 33 countries, in addition to nearly 600,000 isolate genomes, to gain insight into the global prevalence and taxonomic range of clinically relevant AR genes. We find that several of the most concerning AR genes, such as those encoding the cephalosporinase CTX-M and carbapenemases KPC, IMP, NDM, and VIM, remain taxonomically restricted to Proteobacteria. Even cfiA, the most common carbapenemase gene within the human gut microbiome, remains tightly restricted to Bacteroides, despite being found on a mobilizable plasmid. We confirmed these findings in gut microbiome samples from India, Honduras, Pakistan, and Vietnam, using a high-sensitivity single-cell fusion PCR approach. Focusing on a set of genes encoding carbapenemases and cephalosporinases, thus far restricted to Bacteroides species, we find that few mutations are required for efficacy in a different phylum, raising the question of why these genes have not spread more widely. Overall, these data suggest that globally prevalent, clinically relevant AR genes have not yet established themselves across diverse commensal gut microbiota.

The enmity paradox.

The "friendship paradox" of social networks states that, on average, "your friends have more friends than you do". Here, we theoretically and empirically explore a related and overlooked paradox we refer to as the "enmity paradox". We use empirical data from 24,678 people living in 176 villages in rural Honduras. We empirically show that, for a real negative undirected network (created by symmetrizing antagonistic interactions), the paradox exists as it does in the positive world. Specifically, a person's enemies have more enemies, on average, than a person does. Furthermore, in a mixed world of positive and negative ties, we study the conditions for the existence of the paradox, which we refer to as the "mixed-world paradox", both theoretically and empirically, finding that, for instance, a person's friends typically have more enemies than a person does. We also confirm the "generalized" enmity paradox for non-topological attributes in real data, analogous to the generalized friendship paradox (e.g., the claim that a person's enemies are richer, on average, than a person is). As a consequence, the naturally occurring variance in the degree distribution of both friendship and antagonism in social networks can skew people's perceptions of the social world.

Mass gatherings for political expression had no discernible association with the local course of the COVID-19 pandemic in the USA in 2020 and 2021.

Epidemic disease can spread during mass gatherings. We assessed the impact of a type of mass gathering about which comprehensive data were available on the local-area trajectory of the COVID-19 epidemic. Here we examined five types of political event in 2020 and 2021: the US primary elections, the US Senate special election in Georgia, the gubernatorial elections in New Jersey and Virginia, Donald Trump's political rallies and the Black Lives Matter protests. Our study period encompassed over 700 such mass gatherings during multiple phases of the pandemic. We used data from the 48 contiguous states, representing 3,108 counties, and we implemented a novel extension of a recently developed non-parametric, generalized difference-in-difference estimator with a (high-quality) matching procedure for panel data to estimate the average effect of the gatherings on local mortality and other outcomes. There were no statistically significant increases in cases, deaths or a measure of epidemic transmissibility (Rt) in a 40-day period following large-scale political activities. We estimated small and statistically non-significant effects, corresponding to an average difference of -0.0567 deaths (95% CI = -0.319, 0.162) and 8.275 cases (95% CI = -1.383, 20.7) on each day for counties that held mass gatherings for political expression compared to matched control counties. In sum, there is no statistical evidence of a material increase in local COVID-19 deaths, cases or transmissibility after mass gatherings for political expression during the first 2 years of the pandemic in the USA. This may relate to the specific manner in which such activities are typically conducted.

AI and the transformation of social science research.

Careful bias management and data fidelity are key.

Social network correlates of free and purchased insecticide-treated bed nets in rural Uganda.

BACKGROUND: Malaria is a major cause of mortality and morbidity in Uganda. Despite Uganda's efforts to distribute bed nets, only half of households have achieved the World Health Organization (WHO) Universal Coverage Criteria (one bed net for every two household members). The role of peer influence on bed net ownership remains underexplored. Data on the complete social network of households were collected in a rural parish in southwestern Uganda to estimate the association between household bed net ownership and peer household bed net ownership. METHODS: Data on household sociodemographics, bed net ownership, and social networks were collected from all households across one parish in southwestern Uganda. Bed nets were categorized as either purchased or free. Purchased and free bed net ownership ratios were calculated based on the WHO Universal Coverage Criteria. Using network name generators and complete census of parish residents, the complete social network of households in the parish was generated. Linear regression models that account for network autocorrelation were fitted to estimate the association between households' bed net ownership ratios and bed net ownership ratios of network peer households, adjusting for sociodemographics and network centrality. RESULTS: One thousand seven hundred forty-seven respondents were interviewed, accounting for 716 households. The median number of peer households to which a household was directly connected was 7. Eighty-six percent of households owned at least one bed net, and 41% of households met the WHO Universal Coverage Criterion. The median bed net ownership ratios were 0.67 for all bed nets, 0.33 for free bed nets, and 0.20 for purchased bed nets. In adjusted multivariable models, purchased bed net ownership ratio was associated with average household wealth among peer households (b = 0.06, 95% CI 0.03, 0.10), but not associated with average purchased bed net ownership ratio of peer households. Free bed net ownership ratio was associated with the number of children under 5 (b = 0.08, 95% CI 0.05, 0.10) and average free bed net ownership ratios of peer households (b = 0.66, 95% CI 0.46, 0.85). CONCLUSIONS: Household bed net ownership was associated with bed net ownership of peer households for free bed nets, but not for purchased bed nets. The findings suggest that public health interventions may consider leveraging social networks as tools for dissemination, particularly for bed nets that are provided free of charge.

Polarized Citizen Preferences for the Ethical Allocation of Scarce Medical Resources in 20 Countries.

Objective. When medical resources are scarce, clinicians must make difficult triage decisions. When these decisions affect public trust and morale, as was the case during the COVID-19 pandemic, experts will benefit from knowing which triage metrics have citizen support. Design. We conducted an online survey in 20 countries, comparing support for 5 common metrics (prognosis, age, quality of life, past and future contribution as a health care worker) to a benchmark consisting of support for 2 no-triage mechanisms (first-come-first-served and random allocation). Results. We surveyed nationally representative samples of 1000 citizens in each of Brazil, France, Japan, and the United States and also self-selected samples from 20 countries (total N = 7599) obtained through a citizen science website (the Moral Machine). We computed the support for each metric by comparing its usability to the usability of the 2 no-triage mechanisms. We further analyzed the polarizing nature of each metric by considering its usability among participants who had a preference for no triage. In all countries, preferences were polarized, with the 2 largest groups preferring either no triage or extensive triage using all metrics. Prognosis was the least controversial metric. There was little support for giving priority to healthcare workers. Conclusions. It will be difficult to define triage guidelines that elicit public trust and approval. Given the importance of prognosis in triage protocols, it is reassuring that it is the least controversial metric. Experts will need to prepare strong arguments for other metrics if they wish to preserve public trust and morale during health crises. Highlights: We collected citizen preferences regarding triage decisions about scarce medical resources from 20 countries.We find that citizen preferences are universally polarized.Citizens either prefer no triage (random allocation or first-come-first served) or extensive triage using all common triage metrics, with "prognosis" being the least controversial.Experts will need to prepare strong arguments to preserve or elicit public trust in triage decisions.

Algorithms for seeding social networks can enhance the adoption of a public health intervention in urban India.

Targeting structurally influential individuals within social networks can enhance adoption of health interventions within populations. We tested the effectiveness of two algorithms to improve social contagion that do not require knowledge of the whole network structure. We mapped the social interactions of 2,491 women in 50 residential buildings (chawls) in Mumbai, India. The buildings, which are social units, were randomized to (1) targeting 20% of the women at random, (2) targeting friends of such randomly chosen women, (3) targeting pairs of people composed of randomly chosen women and a friend, or (4) no targeting. Both targeting algorithms, friendship nomination and pair targeting, enhanced adoption of a public health intervention related to the use of iron-fortified salt for anemia. In particular, the targeting of pairs of friends, which is relatively easily implementable in field settings, enhanced adoption of novel practices through both social influence and social reinforcement.

Characterizing super-spreaders using population-level weighted social networks in rural communities.

Sociocentric network maps of entire populations, when combined with data on the nature of constituent dyadic relationships, offer the dual promise of advancing understanding of the relevance of networks for disease transmission and of improving epidemic forecasts. Here, using detailed sociocentric data collected over 4 years in a population of 24 702 people in 176 villages in Honduras, along with diarrhoeal and respiratory disease prevalence, we create a social-network-powered transmission model and identify super-spreading nodes as well as the nodes most vulnerable to infection, using agent-based Monte Carlo network simulations. We predict the extent of outbreaks for communicable diseases based on detailed social interaction patterns. Evidence from three waves of population-level surveys of diarrhoeal and respiratory illness indicates a meaningful positive correlation with the computed super-spreading capability and relative vulnerability of individual nodes. Previous research has identified super-spreaders through retrospective contact tracing or simulated networks. By contrast, our simulations predict that a node's super-spreading capability and its vulnerability in real communities are significantly affected by their connections, the nature of the interaction across these connections, individual characteristics (e.g. age and sex) that affect a person's ability to disperse a pathogen, and also the intrinsic characteristics of the pathogen (e.g. infectious period and latency). This article is part of the theme issue 'Data science approach to infectious disease surveillance'.

Household food insecurity and health in a high-migration area in rural Honduras.

Household food insecurity (HFI) is a significant problem in the developing world. Relationships between HFI and nutrition, physical growth, and development have been elucidated; less is known about the non-nutritional impacts among individuals living in rural areas in low-income countries. The aim of this study was to determine if HFI is a risk factor for suboptimal mental health and overall health in rural Honduras. In a population of 24,696 adults with 176 isolated villages in western Honduras, we collected data on household food insecurity and physical and mental health outcome measures. Using logistic regression with and without adjusting for village and household level unobservables invariant across individual respondents, we show that females (OR: 1.11, p <0.01)), indigenous people (OR: 2:00, p < 0.01), and those planning to migrate (OR: 1.24, p <0.01) have higher odds of experiencing food insecurity. The risks of food insecurity and poor health were mitigated among respondents living where they were born and having multi-generations of relatives living in the same village-a measure of the opportunity and availability of social networks. Living in a food insecure compared to a food secure household was associated with 77 percent higher odds of being depressed, 35 percent higher odds of low overall mental health, and 20 percent higher odds for low overall health.

Triadic embeddedness structure in family networks predicts mobile communication response to a sudden natural disaster.

Kinship networks are a fundamental social unit in human societies, and like social networks in general, provide social support in times of need. Here, we investigate the impact of sudden environmental shock, the Ms 7.0 2013 Ya'an earthquake, on the mobile communications patterns of local families, which we operationalize using anonymized individual-level mobile telecommunications metadata from family plan subscribers of a major carrier (N = 35,565 people). We demonstrate that families' communications dynamics after the earthquake depended on their triadic embeddedness structure, a structural metric we propose that reflects the number of dyads in a family triad that share social ties. We find that individuals in more embedded family structures were more likely to first call other family plan members and slower in calling non-family ties immediately after the earthquake; these tendencies were stronger at higher earthquake intensity. In the weeks after the event, individuals in more embedded family structures had more reciprocal communications and contacted more social ties in their broader social network. Overall, families that are structurally more embedded displayed higher levels of intra-family coordination and mobilization of non-family social connections.

Using Trellis software to enhance high-quality large-scale network data collection in the field.

Trellis is a mobile platform created by the Human Nature Lab at the Yale Institute for Network Science to collect high-quality, location-aware, off-line/online, multi-lingual, multi-relational social network and behavior data in hard-to-reach communities. Respondents use Trellis to identify their social contacts by name and photograph, a procedure especially useful in low-literacy populations or in contexts where names may be similar or confusing. We use social network data collected from 1,969 adult respondents in two villages in Kenya to demonstrate Trellis' ability to provide unprecedented metadata to monitor and report on the data collection process including artifactual variability based on surveyors, time of day, or location.

CurmElo: The theory and practice of a forced-choice approach to producing preference rankings.

We introduce CurmElo, a forced-choice approach to producing a preference ranking of an arbitrary set of objects that combines the Elo algorithm with novel techniques for detecting and correcting for (1) preference heterogeneity induced polarization in preferences among raters, and (2) intransitivity in preference rankings. We detail the application of CurmElo to the problem of generating approximately preference-neutral identifiers, in this case four-letter and five-letter nonsense words patterned on the phonological conventions of the English language, using a population of Amazon Mechanical Turk workers. We find evidence that human raters have significant non-uniform preferences over these nonsense words, and we detail the consequences of this finding for social science work that utilizes identifiers without accounting for the bias this can induce. In addition, we describe how CurmElo can be used to produce rankings of arbitrary features or dimensions of preference of a set of objects relative to a population of raters.

Network Engineering Using Autonomous Agents Increases Cooperation in Human Groups.

Cooperation in human groups is challenging, and various mechanisms are required to sustain it, although it nevertheless usually decays over time. Here, we perform theoretically informed experiments involving networks of humans (1,024 subjects in 64 networks) playing a public-goods game to which we sometimes added autonomous agents (bots) programmed to use only local knowledge. We show that cooperation can not only be stabilized, but even promoted, when the bots intervene in the partner selections made by the humans, re-shaping social connections locally within a larger group. Cooperation rates increased from 60.4% at baseline to 79.4% at the end. This network-intervention strategy outperformed other strategies, such as adding bots playing tit-for-tat. We also confirm that even a single bot can foster cooperation in human groups by using a mixed strategy designed to support the development of cooperative clusters. Simple artificial intelligence can increase the cooperation of groups.

Collective communication and behaviour in response to uncertain 'Danger' in network experiments.

In emergencies, social coordination is especially challenging. People connected with each other may respond better or worse to an uncertain danger than isolated individuals. We performed experiments involving a novel scenario simulating an unpredictable situation faced by a group in which 2480 subjects in 108 groups had to both communicate information and decide whether to 'evacuate'. We manipulated the permissible sorts of interpersonal communication and varied group topology and size. Compared to groups of isolated individuals, we find that communication networks suppress necessary evacuations because of the spontaneous and diffuse emergence of false reassurance; yet, communication networks also restrain unnecessary evacuations in situations without disasters. At the individual level, subjects have thresholds for responding to social information that are sensitive to the negativity, but not the actual accuracy, of the signals being transmitted. Social networks can function poorly as pathways for inconvenient truths that people would rather ignore.

Pay-it-forward gonorrhoea and chlamydia testing among men who have sex with men in China: a randomised controlled trial.

BACKGROUND: WHO recommends that men who have sex with men (MSM) receive gonorrhoea and chlamydia testing, but many evidence-based preventive services are unaffordable. The pay-it-forward strategy offers an individual a gift (eg, a test for sexually transmitted diseases) and then asks whether they would like to give a gift (eg, a future test) to another person. This study examined the effectiveness of a pay-it-forward programme to increase gonorrhoea and chlamydia testing among MSM in China. METHODS: We did a randomised controlled superiority trial at three HIV testing sites run by MSM community-based organisations in Guangzhou and Beijing, China. We included MSM aged 16 years or older who were seeking HIV testing and met indications for gonorrhoea and chlamydia testing. Restricted randomisation was done using computer-generated permuted blocks. 30 groups were randomised into three arms (1:1:1): a pay-it-forward arm in which men were offered free gonorrhoea and chlamydia testing and then asked whether they would like to donate for testing of prospective participants, a pay-what-you-want arm in which men were offered free testing and given the option to pay any desired amount for the test, and a standard-of-care arm in which testing was offered at ¥150 (US$22). There was no masking to arm assignment. The primary outcome was gonorrhoea and chlamydia test uptake ascertained by administrative records. We used generalised estimating equations to estimate intervention effects with one-sided 95% CIs and a prespecified superiority margin of 20%. The trial is registered with ClinicalTrials.gov, NCT03741725. FINDINGS: Between Dec 8, 2018, and Jan 19, 2019, 301 men were recruited and included in the analysis. 101 were randomly assigned to the pay-it-forward group, 100 to the pay-what-you-want group, and 100 to the standard-of-care group. Test uptake for gonorrhoea and chlamydia was 56% (57 of 101 participants) in the pay-it-forward arm, 46% (46 of 100 participants) in the pay-what-you-want arm, and 18% (18 of 100 participants) in the standard-of-care arm. The estimated difference in test uptake between the pay-it-forward and standard-of-care group was 38·4% (95% CI lower bound 28·4%). Among men in the pay-it-forward arm, 54 of 57 (95%) chose to donate to support testing for others. INTERPRETATION: The pay-it-forward strategy can increase gonorrhoea and chlamydia testing uptake among Chinese MSM and could be a useful tool for scaling up preventive services that carry a mandatory fee. FUNDING: US National Institute of Health; Special Programme for Research and Training in Tropical Diseases, sponsored by UNICEF, UNDP, World Bank, and WHO; the National Key Research and Development Program of China; Doris Duke Charitable Foundation; and Social Entrepreneurship to Spur Health.