Modeling DREAMS impact: trends in new HIV diagnoses among women attending antenatal care clinics in DREAMS countries

OBJECTIVES

To understand the impact of United States President's Emergency Plan for AIDS Relief (PEPFAR's) DREAMS (Determined, Resilient, Empowered, AIDS-Free, Mentored, and Safe) Partnership on new HIV diagnoses among women in antenatal care (ANC) settings in 10 African countries from 2015 to 2020.

DESIGN

We modeled spatiotemporal changes in new HIV diagnoses among women in ANC settings using PEPFAR data. Statistical tests were performed in R to compare differences in new diagnoses rates between DREAMS and non-DREAMS subnational units (SNUs) and to explore predictors of new diagnoses declines within DREAMS SNUs.

METHODS

We used a predictive geospatial model to forecast the rate of new diagnoses for each time period in a 5 km grid cell (n = 861 SNUs). Linear model analyses were conducted using predictor variables: urbanicity, DREAMS geographic footprint, 'layering' proxy, and community-level male viral load suppression.

RESULTS

New HIV diagnoses in ANC from 2015 to 2020 declined in nearly all SNUs. 'Always' DREAMS SNUs reported declines of 45% while 'Never' DREAMS SNUs reported a decline of only 37% (F = 8.1, 1 and 829 DF, P < 0.01). Within Always DREAMS SNUs, greater declines were seen in areas with a higher number of minimum services in their DREAMS primary package (t = 2.77, P < 0.01).

CONCLUSION

New HIV diagnoses among women are declining in both DREAMS and non-DREAMS SNUs; mirroring HIV incidence decreases and reflecting increasing community viral load suppression and voluntary male medical circumcision rates. DREAMS programming may have contributed to accelerated declines of new HIV diagnoses in DREAMS SNUs compared with non-DREAMS SNUs. Increased progress is needed to further reduce the disparities between adolescent girls and young women (AGYW) and young men to achieve epidemic control.

Host and viral traits predict zoonotic spillover from mammals

The majority of human emerging infectious diseases are zoonotic, with viruses that originate in wild mammals of particular concern (for example, HIV, Ebola and SARS). Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs. However, few analytical tools exist to identify which host species are likely to harbour the next human virus, or which viruses can cross species boundaries. Here we conduct a comprehensive analysis of mammalian host-virus relationships and show that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy and human population within a species range-which may reflect human-wildlife contact. We demonstrate that bats harbour a significantly higher proportion of zoonotic viruses than all other mammalian orders. We also identify the taxa and geographic regions with the largest estimated number of 'missing viruses' and 'missing zoonoses' and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people.

Host and viral traits predict zoonotic spillover from mammals

Analysis of a comprehensive database of mammalian host–virus relationships reveals that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable and that this enables identification of mammalian species and geographic locations where novel zoonoses are likely to be found.

Zoonotic viruses, many originating in wild mammals, pose a serious threat to global public health. Peter Daszak and colleagues create a comprehensive database of mammalian host–virus relationships, which they analyse to determine patterns of virus and zoonotic virus distribution in mammals. They identify various factors that influence the number and diversity of viruses that infect a given species as well as factors that predict the proportion of zoonotic viruses per species. In doing so, they identify mammalian species and geographic locations where novel zoonoses are likely to be found.

The majority of human emerging infectious diseases are zoonotic, with viruses that originate in wild mammals of particular concern (for example, HIV, Ebola and SARS)^1,2,3. Understanding patterns of viral diversity in wildlife and determinants of successful cross-species transmission, or spillover, are therefore key goals for pandemic surveillance programs⁴. However, few analytical tools exist to identify which host species are likely to harbour the next human virus, or which viruses can cross species boundaries^5,6,7. Here we conduct a comprehensive analysis of mammalian host–virus relationships and show that both the total number of viruses that infect a given species and the proportion likely to be zoonotic are predictable. After controlling for research effort, the proportion of zoonotic viruses per species is predicted by phylogenetic relatedness to humans, host taxonomy and human population within a species range—which may reflect human–wildlife contact. We demonstrate that bats harbour a significantly higher proportion of zoonotic viruses than all other mammalian orders. We also identify the taxa and geographic regions with the largest estimated number of ‘missing viruses’ and ‘missing zoonoses’ and therefore of highest value for future surveillance. We then show that phylogenetic host breadth and other viral traits are significant predictors of zoonotic potential, providing a novel framework to assess if a newly discovered mammalian virus could infect people.

Does the impact of biodiversity differ between emerging and endemic pathogens? The need to separate the concepts of hazard and risk

Biodiversity is of critical value to human societies, but recent evidence that biodiversity may mitigate infectious-disease risk has sparked controversy among researchers. The majority of work on this topic has focused on direct assessments of the relationship between biodiversity and endemic-pathogen prevalence, without disentangling intervening mechanisms; thus study outcomes often differ, fuelling more debate. Here, we suggest two critical changes to the approach researchers take to understanding relationships between infectious disease, both endemic and emerging, and biodiversity that may help clarify sources of controversy. First, the distinct concepts of hazards versus risks need to be separated to determine how biodiversity and its drivers may act differently on each. This distinction is particularly important since it illustrates that disease emergence drivers in humans could be quite different to the general relationship between biodiversity and transmission of endemic pathogens. Second, the interactive relationship among biodiversity, anthropogenic change and zoonotic disease risk, including both direct and indirect effects, needs to be recognized and accounted for. By carefully disentangling these interactions between humans' activities and pathogen circulation in wildlife, we suggest that conservation efforts could mitigate disease risks and hazards in novel ways that complement more typical disease control efforts.This article is part of the themed issue 'Conservation, biodiversity and infectious disease: scientific evidence and policy implications'.

Metacommunity and phylogenetic structure determine wildlife and zoonotic infectious disease patterns in time and space

The potential for disease transmission at the interface of wildlife, domestic animals and humans has become a major concern for public health and conservation biology. Research in this subject is commonly conducted at local scales while the regional context is neglected. We argue that prevalence of infection at local and regional levels is influenced by three mechanisms occurring at the landscape level in a metacommunity context. First, (1) dispersal, colonization, and extinction of pathogens, reservoir or vector hosts, and nonreservoir hosts, may be due to stochastic and niche-based processes, thus determining distribution of all species, and then their potential interactions, across local communities (metacommunity structure). Second, (2) anthropogenic processes may drive environmental filtering of hosts, nonhosts, and pathogens. Finally, (3) phylogenetic diversity relative to reservoir or vector host(s), within and between local communities may facilitate pathogen persistence and circulation. Using a metacommunity approach, public heath scientists may better evaluate the factors that predispose certain times and places for the origin and emergence of infectious diseases. The multidisciplinary approach we describe fits within a comprehensive One Health and Ecohealth framework addressing zoonotic infectious disease outbreaks and their relationship to their hosts, other animals, humans, and the environment.

Bird Migration and Avian Influenza: A Comparison of Hydrogen Stable Isotopes and Satellite Tracking Methods

Satellite-based tracking of migratory waterfowl is an important tool for understanding the potential role of wild birds in the long-distance transmission of highly pathogenic avian influenza. However, employing this technique on a continental scale is prohibitively expensive. This study explores the utility of stable isotope ratios in feathers in examining both the distances traveled by migratory birds and variation in migration behavior. We compared the satellite-derived movement data of 22 ducks from 8 species captured at wintering areas in Bangladesh, Turkey, and Hong Kong with deuterium ratios (δD) of these and other individuals captured at the same locations. We derived likely molting locations from the satellite tracking data and generated expected isotope ratios based on an interpolated map of δD in rainwater. Although δD was correlated with the distance between wintering and molting locations, surprisingly, measured δD values were not correlated with either expected values or latitudes of molting sites. However, population-level parameters derived from the satellite-tracking data, such as mean distance between wintering and molting locations and variation in migration distance, were reflected by means and variation of the stable isotope values. Our findings call into question the relevance of the rainfall isotope map for Asia for linking feather isotopes to molting locations, and underscore the need for extensive ground truthing in the form of feather-based isoscapes. Nevertheless, stable isotopes from feathers could inform disease models by characterizing the degree to which regional breeding populations interact at common wintering locations. Feather isotopes also could aid in surveying wintering locations to determine where high-resolution tracking techniques (e.g. satellite tracking) could most effectively be employed. Moreover, intrinsic markers such as stable isotopes offer the only means of inferring movement information from birds that have died as a result of infection. In the absence of feather based-isoscapes, we recommend a combination of isotope analysis and satellite-tracking as the best means of generating aggregate movement data for informing disease models.

Life history and demographic drivers of reservoir competence for three tick-borne zoonotic pathogens

Animal and plant species differ dramatically in their quality as hosts for multi-host pathogens, but the causes of this variation are poorly understood. A group of small mammals, including small rodents and shrews, are among the most competent natural reservoirs for three tick-borne zoonotic pathogens, Borrelia burgdorferi, Babesia microti, and Anaplasma phagocytophilum, in eastern North America. For a group of nine commonly-infected mammals spanning >2 orders of magnitude in body mass, we asked whether life history features or surrogates for (unknown) encounter rates with ticks, predicted reservoir competence for each pathogen. Life history features associated with a fast pace of life generally were positively correlated with reservoir competence. However, a model comparison approach revealed that host population density, as a proxy for encounter rates between hosts and pathogens, generally received more support than did life history features. The specific life history features and the importance of host population density differed somewhat between the different pathogens. We interpret these results as supporting two alternative but non-exclusive hypotheses for why ecologically widespread, synanthropic species are often the most competent reservoirs for multi-host pathogens. First, multi-host pathogens might adapt to those hosts they are most likely to experience, which are likely to be the most abundant and/or frequently bitten by tick vectors. Second, species with fast life histories might allocate less to certain immune defenses, which could increase their reservoir competence. Results suggest that of the host species that might potentially be exposed, those with comparatively high population densities, small bodies, and fast pace of life will often be keystone reservoirs that should be targeted for surveillance or management.

Spatiotemporal model of barley and cereal yellow dwarf virus transmission dynamics with seasonality and plant competition

Many generalist pathogens are influenced by the spatial distributions and relative abundances of susceptible host species. The spatial structure of host populations can influence patterns of infection incidence (or disease outbreaks), and the effects of a generalist pathogen on host community dynamics in a spatially heterogeneous community may differ from predictions derived via simple models. In this paper, we model the transmission of a generalist pathogen within a patch framework that incorporates the movement of vectors between discrete host patches to investigate the effects of local host community composition and vector movement rates on disease dynamics.We use barley and cereal yellow dwarf viruses (B/CYDV), a suite of generalist, aphid-vectored pathogens of grasses, and their interactions with a range of host species as our case study. We examine whether B/CYDV can persist locally or in a patch framework across a range of host community configurations. We then determine how pathogen-mediated interactions between perennial and annual competitors are altered at the local and regional scale when the host populations are spatially structured. We find that the spatial configuration of the patch system, host composition within patches, and patch connectivity affect not only the ability of the pathogen to invade a fragmented system, but also determine whether the pathogen facilitates the invasion of a non-native host species. Further, our results suggest that connectivity can interact with arrival time and host infection tolerance to determine the success or failure of establishment for newly arriving species.

Predators indirectly control vector-borne disease: linking predator-prey and host-pathogen models

Pathogens transmitted by arthropod vectors are common in human populations, agricultural systems and natural communities. Transmission of these vector-borne pathogens depends on the population dynamics of the vector species as well as its interactions with other species within the community. In particular, predation may be sufficient to control pathogen prevalence indirectly via the vector. To examine the indirect effect of predators on vectored-pathogen dynamics, we developed a theoretical model that integrates predator-prey and host-pathogen theory. We used this model to determine whether predation can prevent pathogen persistence or alter the stability of host-pathogen dynamics. We found that, in the absence of predation, pathogen prevalence in the host increases with vector fecundity, whereas predation on the vector causes pathogen prevalence to decline, or even become extinct, with increasing vector fecundity. We also found that predation on a vector may drastically slow the initial spread of a pathogen. The predator can increase host abundance indirectly by reducing or eliminating infection in the host population. These results highlight the importance of studying interactions that, within the greater community, may alter our predictions when studying disease dynamics. From an applied perspective, these results also suggest situations where an introduced predator or the natural enemies of a vector may slow the rate of spread of an emerging vector-borne pathogen.

Pathogen-induced reversal of native dominance in a grassland community

Disease may play a critical role in invasions by nonnative plants and animals that currently threaten global biodiversity. For example, a generalist viral pathogen has been recently implicated in one of the most extensive plant invasions worldwide, the invasion and domination of California's perennial grasslands by exotic annual grasses. To date, disease has never been quantitatively assessed as a cause of this invasion. Using a model with field-estimated parameters, we demonstrate that pathogen presence was necessary to reverse competitive outcome and to allow exotic annual grass invasion and dominance. Although pathogen-induced reversal of a competitive hierarchy has been suggested as a mechanism of species invasion, here we quantitatively demonstrate the importance of this phenomenon by using field-derived parameters in a dynamical model. Pathogen-mediated reversals in competitive balance may be critically important for understanding past, and predicting future, invasions.

SPATIAL SPREAD OF AN EMERGING INFECTIOUS DISEASE: CONJUNCTIVITIS IN HOUSE FINCHES

In this paper we quantify the rate of spread of the newly emerged pathogen Mycoplasma gallisepticum of the House Finch, Carpodacus mexicanus, in its introduced range. We compare and contrast the rapid, yet decelerating, rate of spread of the pathogen with the slower, yet accelerating rate of spread of the introduced host. Comparing the rate of spread of this pathogen to pathogens in terrestrial mammalian hosts, we see that elevation and factors relating to host abundance restrict disease spread, rather than finding any major effects of discrete barriers or anthropogenic movement. We examine the role of seasonality in the rate of spread, finding that the rate and direction of disease spread relates more to seasonality in host movement than to seasonality in disease prevalence. We conclude that asymptomatic carriers are major transmitters of Mycoplasma gallisepticum into novel locations, a finding which may also be true for many other diseases, such as West Nile Virus and avian influenza.

Dynamics of a novel pathogen in an avian host: Mycoplasmal conjunctivitis in house finches

In early 1994, a novel strain of Mycoplasma gallisepticum (MG)--a poultry pathogen with a world-wide distribution--emerged in wild house finches and within 3 years had reached epidemic proportions across their eastern North American range. The ensuing epizootic resulted in a rapid decline of the host population coupled with considerable seasonal fluctuations in prevalence. To understand the dynamics of this disease system, a multi-disciplinary team composed of biologists, veterinarians, microbiologists and mathematical modelers set forth to determine factors driving and influenced by this host-pathogen system. On a broad geographic scale, volunteer observers ("citizen scientists") collected and reported data used for calculating both host abundance and disease prevalence. The scale at which this monitoring initiative was conducted is unprecedented and it has been an invaluable source of data for researchers at the Cornell Laboratory of Ornithology to track the spread and magnitude of disease both spatially and temporally. At a finer scale, localized and intensive field studies provided data used to quantify the effects of disease on host demographic parameters via capture-mark-recapture modeling, effects of host behavior on disease and vice-versa, and the biological and genetic profiles of birds with known phenotypic characteristics. To balance the field-based component of the study, experiments were conducted with finches held in captivity to describe and quantify the effects of experimental infections on hosts in both individual and social settings. The confluence of these various elements of the investigation provided the foundation for construction of a general compartmentalized epidemiological model of the dynamics of the house finch-MG system. This paper serves several purposes including (i) a basic review of the pathogen, host, and epidemic cycle; (ii) an explanation of our research strategy; (iii) a basic review of results from the diverse multi-disciplinary approaches employed; and (iv) pertinent questions relevant to this and other wildlife disease studies that require further investigation.

Seasonality and wildlife disease: how seasonal birth, aggregation and variation in immunity affect the dynamics of Mycoplasma gallisepticum in house finches

We examine the role of host seasonal breeding, host seasonal social aggregation and partial immunity in affecting wildlife disease dynamics, focusing on the dynamics of house finch conjunctivitis (Mycoplasma gallisepticum (MG) in Carpodacus mexicanus). This case study of an unmanaged emerging infectious disease provides useful insight into the important role of seasonal factors in driving ongoing disease dynamics. Seasonal breeding can force recurrent epidemics through the input of fresh susceptibles, which will clearly affect a wide variety of wildlife disease dynamics. Seasonal patterns of social aggregation and foraging behaviour could change transmission dynamics. We use latitudinal variation in the timing of breeding, and social systems to model seasonal dynamics of house finch conjunctivitis across eastern North America. We quantify the patterns of seasonal breeding, and social aggregation across a latitudinal gradient in the eastern range of the house finch, supplemented with known field and laboratory information on immunity to MG in finches. We then examine the interactions of these factors in a theoretical model of disease dynamics. We find that both forms of seasonality could explain the dynamics of the house finch-MG system, and that these factors could have important effects on the dynamics of wildlife diseases generally. In particular, while either alone is sufficient to create recurrent cycles of prevalence in a population with an endemic disease, both are required to produce the specific semi-annual pattern of disease prevalence seen in the house finch conjunctivitis system.

EXPERIMENTAL INFECTION OF HOUSE FINCHES WITH MYCOPLASMA GALLISEPTICUM

Mycoplasma gallisepticum (MG) has caused an endemic upper respiratory and ocular infection in the eastern house finch (Carpodacus mexicanus) after the epidemic first described in 1994. The disease has been studied by a number of investigators at a population level and reports describe experimental infection in group-housed MG-free house finches. Because detailed observation and evaluation of individual birds in group-housed passerines is problematic, we studied individually housed house finches that were experimentally inoculated with the finch strain of MG in a controlled environment. To accomplish this, a study was conducted spanning the period of November 2001-April 2002 with 20 MG-free (confirmed by the rapid plate agglutination assay and polymerase chain reaction [PCR] assay) eastern house finches captured in the Cayuga Basin area of central New York (USA) in the summer of 2001. After a period of acclimatization and observation (12 wk), 20 finches were inoculated with a 0.05-ml aliquot of MG (3.24 x 10(5) colony-forming units/ml) via bilateral conjunctival sac instillations. Two additional finches acted as controls and were inoculated in the same manner with preservative-free sterile saline solution. After inoculation, all finches except the controls exhibited clinical signs of conjunctivitis within 2-6 days. The progression of the disease was evaluated by several methods, including PCR, behavioral observations, and physical examination including eye scoring, body weight, and body condition index. Over a period of 21 wk, MG-infected finches developed signs of disease and recovered (80%), developed signs of disease and progressed to become chronically infected (15%), or died (5%). We hypothesize that the high survival rate and recovery of these finches after infection was associated with the use of controlled environmental conditions, acclimatization, a high plane of nutrition, and low stocking (housing) density, all of which are factors documented to be important in the outcome of MG infections in domestic poultry and other species.

How localized consumption stabilizes predator-prey systems with finite frequency of mixing

Predator-prey theory began with aspatial models that assumed organisms interacted as if they were "well-mixed" particles that obey the laws of mass action, but it has become clear that both the spatial and individual nature of many organisms can change how the dynamics of such systems function. Here I examine how localized consumption of prey by predators changes the dynamics of predator-prey systems; I use an individual-based simulation of the Rosenzweig-MacArthur model in implicit space and its mean-field approximation. In combination with limited movement, localized consumption makes the predator-prey dynamics more stable than the comparable "well-mixed" Rosenzweig-MacArthur model. Using a spatial correlation, one can directly compare a simplified version of the individual-based model with the Rosenzweig-MacArthur model. While this comparison allows the changes in the dynamics to be captured by the "well-mixed" Rosenzweig-MacArthur model, the parameters of the functional response are now dependent on the movement parameters, and so the functional response must be estimated statistically from the dynamics of the individual-based model. Yet this implies that aspatial models may work in a scale-specific fashion for spatial systems. Unlike many recent spatial models, the localized consumption and limited movement in the model presented here cannot produce coherent spatial patterns and do not depend on a patchy structure, as found in metapopulation models. Instead, the individual nature of the interactions creates a diffusion-limited reaction, which appears closer to a form of ephemeral refuge.

Habitat structure and population persistence in an experimental community

Understanding spatial population dynamics is fundamental for many questions in ecology and conservation. Many theoretical mechanisms have been proposed whereby spatial structure can promote population persistence, in particular for exploiter-victim systems (host-parasite/pathogen, predator-prey) whose interactions are inherently oscillatory and therefore prone to extinction of local populations. Experiments have confirmed that spatial structure can extend persistence, but it has rarely been possible to identify the specific mechanisms involved. Here we use a model-based approach to identify the effects of spatial population processes in experimental systems of bean plants (Phaseolus lunatus), herbivorous mites (Tetranychus urticae) and predatory mites (Phytoseiulus persimilis). On isolated plants, and in a spatially undivided experimental system of 90 plants, prey and predator populations collapsed; however, introducing habitat structure allowed long-term persistence. Using mechanistic models, we determine that spatial population structure did not contribute to persistence, and spatially explicit models are not needed. Rather, habitat structure reduced the success of predators at locating prey outbreaks, allowing between-plant asynchrony of local population cycles due to random colonization events.