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Abstract The One Health approach, which assesses the interconnectedness of animal, human, and environmental health, fails to include and amplify Indigenous knowledge and Indigenous scientists. To effectively center Indigenous knowledge next to and within the One Health approach, which is historically based in Western science, the similarities and differences between Indigenous science, specifically Traditional Ecological Knowledge (TEK), and One Health must be explored. The objective of this project is to identify values in Indigenous science that are unsupported or underrepresented in Western science and then collaboratively ideate recommendations that Western allies can take to center and support Indigenous scientists and elevate Indigenous knowledge. From January to March 2023, the study team conducted semi-structured interviews with Indigenous knowledge keepers via Zoom video calls. American Indian, Alaska Native, Native Hawaiian (Kānaka Maoli), and other Indigenous participants from the global diaspora residing in the continental United States and Hawaiian Islands were recruited through social media and referrals from Indigenous leaders who had participated in formative (phase 1) interviews completed in 2022. In those formative interviews, four themes emerged and called for further exploration of Indigenous perspectives on (1) the natural world, (2) cultural heritage, (3) value expression, and (4) reflection. These ideas were reframed into questions asked in subsequent (phase 2) interviews in 2023. Thematic identification methods were used to highlight key ideas throughout the interviews. Participants noted gaps between their Indigenous worldviews and the One Health model, particularly relating to contrasts with Western culture, holistic expression, power in action, identity and belonging, maintaining community and cultural practices, and sharing information/education. It was also noted that One Health must do more than just uplift Indigenous values to support Indigenous scientists and should instead collaborate with TEK keepers and foster practices that are inclusive and validating of other knowledge systems. Phase 2 interview responses highlighted Indigenous principles that are underrepresented in One Health practice. These principles were transformed into considerations specifically for Western-rooted scientists to improve allyship to Indigenous science and scientists. Adoption of the considerations would strengthen partnership between One Health practitioners and Indigenous scientists and promote collaboration across many ways of knowing. One Health impact statement The One Health theory encourages transdisciplinary collaboration to break down siloing and innovate solutions. Yet, One Health practice, and the Western scientific approach it takes, often excludes involvement with Indigenous ways of knowing and disclaims Indigenous knowledge keepers who have been conducting “One Health” work since time immemorial. Indigenous knowledge keepers who self-identified as cultural bridges between Native communities and Western communities were interviewed and asked to speak to values found in Indigenous science and research. The featured principles highlight some of the similarities and differences between Indigenous and Western scientific approaches. The identified values informed recommendations for Western scientists to be better allies to Indigenous scientists and to amplify Indigenous voices and science. One Health practitioners will benefit from these guidelines by navigating research in a more equitable way and by creating sustainable reciprocal partnerships with Indigenous scientists. This makes One Health more open and accessible to Indigenous and Western ways of knowing.

The One Health conceptual framework envisions human, animal, and environmental health as interconnected. This framework has achieved remarkable progress in the control of zoonotic diseases, but it commonly neglects the environmental domain, implicitly prioritizes human life over the life of other beings, and fails to consider the political, cultural, social, historical, and economic contexts that shape the health of multispecies collectives. We have developed a novel theoretical framework, Relational One Health, which expands the boundaries of One Health, clearly defines the environmental domain, and provides an avenue for engagement with critical theory. We present a systematic literature review of One Health frameworks to demonstrate the novelty of Relational One Health, and to orient it with respect to other critically-engaged frameworks for One Health. Our results indicate that while Relational One Health complements several earlier frameworks, these other frameworks are either not intended for research, or for narrow sets of research questions. We then demonstrate the utility of Relational One Health for One Health research through case studies in Brazil, Israel, and Ethiopia. Empirical research which is grounded in theory can speak collectively, increasing the impact of individual studies and the field as a whole. One Health is uniquely poised to address several wicked challenges facing the 21st century—climate change, pandemics, neglected zoonoses, and biodiversity collapse—and a unifying theoretical tradition is key to generating the evidence needed to meet these challenges.

Abstract The One Health Clinic (OHC) is a transdisciplinary approach to healthcare services delivery, providing low-barrier healthcare and community services for people experiencing homelessness (PEH) and their companion animals that integrate human, animal, and environmental health. This study aimed to determine the effectiveness of an OHC model in a youth and young adult shelter on access to healthcare, housing, and community resources. Researchers conducted semi-structured interviews with six OHC client participants and three provider participants, and a thematic analysis was used to study the effects of the OHC model on two key outcomes: overall health for humans and their companion animal(s), and access to public services for humans and their companion animal(s). Results showed that the OHC model provides multiple services in one place which reduces barriers to accessing health services, housing, and community resources. The integrated healthcare services promote positive interactions with providers and facilitate access to healthcare, housing, and community resources for PEH and their companion animals. Settings with similar goals of client health and access to healthcare, as well as housing services and community resources, can utilize the OHC care model to integrate services for lower barrier access to healthcare and community services to promote health on an individual level and from a One Health perspective. One Health impact statement Our study on the OHC model demonstrates the tangible impact of integrating healthcare services for homeless young adults and their companion animals. In the One Health context, our work addresses the complex interplay between human, animal, and environmental well-being. By bridging healthcare, housing, and community resources, the OHC model enhances access and reduces barriers. The One Health approach enriches impact, as collaboration across sectors yields multifaceted benefits. The transdisciplinary nature of our research fuses academic and non-academic knowledge, ensuring a holistic perspective. Practical solutions emerge from diverse insights, transcending traditional boundaries. This co-produced transformational knowledge facilitates real-world change, impacting lives, promoting resilience, and fostering sustainability. The OHC model exemplifies how cooperative, transdisciplinary efforts yield breakthroughs that elevate health, save lives, and nurture the optimal environment for people and their companion animals to live, work, and play.

SARS-CoV-2 likely emerged from an animal reservoir. However, the frequency of and risk factors for interspecies transmission remain unclear. We conducted a community-based study in Idaho, USA, of pets in households that had >1 confirmed SARS-CoV-2 infections in humans. Among 119 dogs and 57 cats, clinical signs consistent with SARS-CoV-2 were reported for 20 dogs (21%) and 19 cats (39%). Of 81 dogs and 32 cats sampled, 40% of dogs and 43% of cats were seropositive, and 5% of dogs and 8% of cats were PCR positive. This discordance might be caused by delays in sampling. Respondents commonly reported close human‒animal contact and willingness to take measures to prevent transmission to their pets. Reported preventive measures showed a slightly protective but nonsignificant trend for both illness and seropositivity in pets. Sharing of beds and bowls had slight harmful effects, reaching statistical significance for sharing bowls and seropositivity.

Abstract More than one billion people rely on livestock for income, nutrition, and social cohesion, however livestock keeping can facilitate disease transmission and contribute to climate change. While data on the distribution of livestock have broad utility across a range of applications, efforts to map the distribution of livestock on a large scale are limited to the Gridded Livestock of the World (GLW) project. We present a complimentary effort to map the distribution of cattle and pigs in Malawi, Uganda, Democratic Republic of Congo, and South Sudan. In contrast to GLW, which uses dasymmetric modeling applied to census data to produce time-stratified estimates of livestock counts and spatial density, our work uses complex survey data and distinct modeling methods to generate a time-series of livestock distribution, defining livestock density as the ratio of animals to humans. In addition to favorable cross-validation results and general agreement with national density estimates derived from external data on national human and livestock populations, our results demonstrate extremely good agreement with GLW-3 estimates, supporting the validity of both efforts. Our results furthermore offer a high-resolution time series result and employ a definition of density which is particularly well-suited to the study of livestock-origin zoonoses.

Abstract Background A proactive approach to preventing and responding to emerging infectious diseases is critical to global health security. We present a three-stage approach to modeling the spatial distribution of outbreak vulnerability to Aedes aegypti-vectored diseases in Perú. Methods Extending a framework developed for modeling hemorrhagic fever vulnerability in Africa, we modeled outbreak vulnerability in three stages: index case potential (stage 1), outbreak receptivity (stage 2), and epidemic potential (stage 3), stratifying scores on season and El Niño events. Subsequently, we evaluated the validity of these scores using dengue surveillance data and spatial models. Results We found high validity for stage 1 and 2 scores, but not stage 3 scores. Vulnerability was highest in Selva Baja and Costa, and in summer and during El Niño events, with index case potential (stage 1) being high in both regions but outbreak receptivity (stage 2) being generally high in Selva Baja only. Conclusions Stage 1 and 2 scores are well-suited to predicting outbreaks of Ae. aegypti-vectored diseases in this setting, however stage 3 scores appear better suited to diseases with direct human-to-human transmission. To prevent outbreaks, measures to detect index cases should be targeted to both Selva Baja and Costa, while Selva Baja should be prioritized for healthcare system strengthening. Successful extension of this framework from hemorrhagic fevers in Africa to an arbovirus in Latin America indicates its broad utility for outbreak and pandemic preparedness and response activities.

Domestic and wild animals are important reservoirs of the rhodesiense form of human African trypanosomiasis (rHAT), however quantification of this effect offers utility for deploying non-medical control activities, and anticipating their success when wildlife are excluded. Further, the uncertain role of animal reservoirs-particularly pigs-threatens elimination of transmission (EOT) targets set for the gambiense form (gHAT). Using a new time series of high-resolution cattle and pig density maps, HAT surveillance data collated by the WHO Atlas of HAT, and methods drawn from causal inference and spatial epidemiology, we conducted a retrospective ecological cohort study in Uganda, Malawi, Democratic Republic of the Congo (DRC) and South Sudan to estimate the effect of cattle and pig density on HAT risk. For rHAT, we found a positive effect for cattle (RR 1.61, 95% CI 0.90, 2.99) and pigs (RR 2.07, 95% CI 1.15, 2.75) in Uganda, and a negative effect for cattle (RR 0.88, 95% CI 0.71, 1.10) and pigs (RR 0.42, 95% CI 0.23, 0.67) in Malawi. For gHAT we found a negative effect for cattle in Uganda (RR 0.88, 95% CI 0.50, 1.77) and South Sudan (RR 0.63, 95% CI 0.54, 0.77) but a positive effect in DRC (1.17, 95% CI 1.04, 1.32). For pigs, we found a positive gHAT effect in both Uganda (RR 2.02, 95% CI 0.87, 3.94) and DRC (RR 1.23, 95% CI 1.10, 1.37), and a negative association in South Sudan (RR 0.66, 95% CI 0.50, 0.98). These effects did not reach significance for the cattle-rHAT effect in Uganda or Malawi, or the cattle-gHAT and pig-gHAT effects in Uganda. While ecological bias may drive the findings in South Sudan, estimated E-values and simulation studies suggest unmeasured confounding and underreporting are unlikely to explain our findings in Malawi, Uganda, and DRC. Our results suggest cattle and pigs may be important reservoirs of rHAT in Uganda but not Malawi, and that pigs-and possibly cattle-may be gHAT reservoirs.

BackgroundDengue fever is the most common arboviral disease in humans, with an estimated 50-100 million annual infections worldwide. Dengue fever cases have increased substantially in the past four decades, driven largely by anthropogenic factors including climate change. More than half the population of Peru is at risk of dengue infection and due to its geography, Peru is also particularly sensitive to the effects of El Niño Southern Oscillation (ENSO). Determining the effect of ENSO on the risk for dengue outbreaks is of particular public health relevance and may also be applicable to other Aedes-vectored viruses.MethodsWe conducted a time-series analysis at the level of the district-month, using surveillance data collected from January 2000 to September 2018 from all districts with a mean elevation suitable to survival of the mosquito vector (ResultsWe detected a positive and significant effect of temperature (°C, RR 1.14, 95% CI 1.13, 1.15, adjusted for precipitation) and ENSO (ICEN index: RR 1.17, 95% CI 1.15, 1.20; ONI index: RR 1.04, 95% CI 1.02, 1.07) on outbreak risk, but no evidence of a strong effect for precipitation after adjustment for temperature. Both natural region and season were found to be significant effect modifiers of the ENSO-dengue effect, with the effect of ENSO being stronger in the summer and the Selva Alta and Costa regions, compared with winter and Selva Baja and Sierra regions.ConclusionsOur results provide strong evidence that temperature and ENSO have significant effects on dengue outbreaks in Peru, however these results interact with region and season, and are stronger for local ENSO impacts than remote ENSO impacts. These findings support optimization of a dengue early warning system based on local weather and climate monitoring, including where and when to deploy such a system and parameterization of ENSO events, and provide high-precision effect estimates for future climate and dengue modeling efforts.

Summary: Background: Dual HIV and syphilis testing might help to prevent mother-to-child transmission (MTCT) of HIV and syphilis through increased case detection and treatment. We aimed to model and assess the cost-effectiveness of dual testing during antenatal care in four countries with varying HIV and syphilis prevalence. Methods: In this modelling study, we developed Markov models of HIV and syphilis in pregnant women to estimate costs and infant health outcomes of maternal testing at the first antenatal care visit with individual HIV and syphilis tests (base case) and at the first antenatal care visit with a dual rapid diagnostic test (scenario one). We additionally evaluated retesting during late antenatal care and at delivery with either individual tests (scenario two) or a dual rapid diagnosis test (scenario three). We modelled four countries: South Africa, Kenya, Colombia, and Ukraine. Strategies with an incremental cost-effectiveness ratio (ICER) less than the country-specific cost-effectiveness threshold (US$500 in Kenya, $750 in South Africa, $3000 in Colombia, and $1000 in Ukraine) per disability-adjusted life-year averted were considered cost-effective. Findings: Routinely offering testing at the first antenatal care visit with a dual rapid diagnosis test was cost-saving compared with the base case in all four countries (ICER: –$26 in Kenya,–$559 in South Africa, –$844 in Colombia, and –$454 in Ukraine). Retesting during late antenatal care with a dual rapid diagnostic test (scenario three) was cost-effective compared with scenario one in all four countries (ICER: $270 in Kenya, $260 in South Africa, $2207 in Colombia, and $205 in Ukraine). Interpretation: Incorporating dual rapid diagnostic tests in antenatal care can be cost-saving across countries with varying HIV prevalence. Countries should consider incorporating dual HIV and syphilis rapid diagnostic tests as the first test in antenatal care to support efforts to eliminate MTCT of HIV and syphilis. Funding: WHO, US Agency for International Development, and the Bill & Melinda Gates Foundation.

Background: Human and animal African trypanosomiases impose a large economic and health burden in their endemic regions. Large strides have been made in the control of human African trypanosomiasis (HAT), yet these efforts have largely focused on the non-zoonotic form of the disease. Using a mathematical model with a 10 year time horizon, we demonstrate the role of the cattle treatment with trypanocides in the epidemiology of zoonotic and non-zoonotic HAT in Uganda, and its potential implications on elimination and eradication of the disease. Methodology/principal findings: We created two compartmental, deterministic models, each comprised of three sub-models: humans, the tsetse fly vector (Glossina fuscipes fuscipes), and cattle. We applied these models to two HAT foci in Uganda: the gambiense (chronic, non-zoonotic) form in the Northern Region, and the rhodesiense (acute, zoonotic) form in the Eastern Region. Parameters were derived from prior literature or assumed. In both foci we assumed G. fuscipes fuscipes expresses zoophilic biting behavior.With trypanocide treatment of cattle administered every 3 months, treatment in stage I (representing engagement in active or passive surveillance) had a larger impact on HAT burden than cattle treatment coverage. However increasing cattle treatment coverage allowed for further reduction in prevalence in both foci. Using these model parameters, our estimated R0 suggests humans cannot alone sustain the HAT epidemic in Uganda. Conclusions/significance: Even in the absence of zoonotic transmission, loss of a preferred tsetse host species can affect HAT risk. Thus One Health strategies which integrate HAT and animal African trypanosomiasis control may improve the timeliness and sustainability of gHAT and rHAT elimination and eradication in Uganda. Furthermore, such strategies reduce the burden of a high-morbidity livestock disease of economic importance. Keywords: Human African trypanosomiasis, Animal African trypanosomiasis, Cattle, Zoonoses, One Health, Mathematical modeling

BackgroundPediatric diarrhea, a leading cause of under-five mortality, is predominantly infectious in etiology. As many putative causal agents are zoonotic, animal exposure is a likely risk factor. To evaluate the effect of animal-related factors on moderate to severe childhood diarrhea in rural Kenya, where animal contact is common, Conan et al. studied 73 matched case-control pairs from 2009-2011, collecting rich exposure data on many dimensions of animal contact. We review the challenges associated with analyzing moderately-sized datasets with a large number of predictors and present two alternative methodological approaches.Methodology/principal findingsWe conducted a simulation study to demonstrate that forward stepwise selection results in overfit models when data are high-dimensional, and that p values reported directly from the data used to train these models are misleading. We described how automated methods of variable selection, attractive when the number of predictors is large, can result in overadjustment bias. We proposed an alternative a priori regression approach not subject to this bias. Applied to Conan et al.'s data, this approach found a non-significant but positive trend for household's sharing of water sources with livestock or poultry, child's presence for poultry slaughter, and child's habit of playing where poultry sleep or defecate. For many predictors evaluated few pairs were discordant, suggesting matching compromised the power of this analysis. Finally, we proposed latent variable modeling as a complimentary approach and performed Item Response Theory modeling on Conan et al.'s data, with animal contact as the latent trait. We found a moderate but non-significant effect (OR 1.21, 95% CI 0.78, 1.87, unit = 1 standard deviation).Conclusions/significanceAutomated methods of model selection are appropriate for prediction models when fit and evaluated on separate samples. However when the goal is inference, these methods can produce misleading results. Furthermore, case-control matching should be done with caution.