Spatial parasite ecology and epidemiology: a review of methods and applications

Caterpillar movement mediates spatially local interactions and determines the relationship between population density and contact

BACKGROUND

While interactions in nature are inherently local, ecological models often assume homogeneity across space, allowing for generalization across systems and greater mathematical tractability. Density-dependent disease models are a prominent example of models that assume homogeneous interactions, leading to the prediction that disease transmission will scale linearly with population density. In this study, we examined how the scale of larval butterfly movement interacts with the resource landscape to influence the relationship between larval contact and population density in the Baltimore checkerspot (Euphydryas phaeton). Our study was inspired by the recent discovery of a viral pathogen that is transmitted horizontally among Baltimore checkerspot larvae.

METHODS

We used multi-year larvae location data across six Baltimore checkerspot populations in the eastern U.S. to test whether larval nests are spatially clustered. We then integrated these spatial data with larval movement data in different resource contexts to investigate whether heterogeneity in spatially local interactions alters the assumed linear relationship between larval nest density and contact. We used Correlated Random Walk (CRW) models and field observations of larval movement behavior to construct Probability Distribution Functions (PDFs) of larval dispersal, and calculated the overlap in these PDFs to estimate conspecific contact within each population.

RESULTS

We found that all populations exhibited significant spatial clustering in their habitat use. Subsequent larval movement rates were influenced by encounters with host plants and larval age, and under many movement scenarios, the scale of predicted larval movement was not sufficient to allow for the "homogeneous mixing" assumed in density dependent disease models. Therefore, relationships between population density and larval contact were typically non-linear. We also found that observed use of available habitat patches led to significantly greater contact than would occur if habitat use were spatially random.

CONCLUSIONS

These findings strongly suggest that incorporating larval movement and spatial variation in larval interactions is critical to modeling disease outcomes in E. phaeton. Epidemiological models that assume a linear relationship between population density and larval contact have the potential to underestimate transmission rates, especially in small populations that are already vulnerable to extinction.

Bartonella infections are prevalent in rodents despite efficient immune responses

BACKGROUND

Pathogens face strong selection from host immune responses, yet many host populations support pervasive pathogen populations. We investigated this puzzle in a model system of Bartonella and rodents from Israel's northwestern Negev Desert. We chose to study this system because, in this region, 75-100% of rodents are infected with Bartonella at any given time, despite an efficient immunological response. In this region, Bartonella species circulate in three rodent species, and we tested the hypothesis that at least one of these hosts exhibits a waning immune response to Bartonella, which allows reinfections.

METHODS

We inoculated captive animals of all three rodent species with the same Bartonella strain, and we quantified the bacterial dynamics and Bartonella-specific immunoglobulin G antibody kinetics over a period of 139 days after the primary inoculation, and then for 60 days following reinoculation with the same strain.

RESULTS

Contrary to our hypothesis, we found a strong, long-lasting immunoglobulin G antibody response, with protective immunological memory in all three rodent species. That response prevented reinfection upon exposure of the rodents to the same Bartonella strain.

CONCLUSIONS

This study constitutes an initial step toward understanding how the interplay between traits of Bartonella and their hosts influences the epidemiological dynamics of these pathogens in nature.

The challenges of detecting Taenia solium and neurocysticercosis in low and middle-income countries: A scoping review of Lao People's Democratic Republic

OBJECTIVE

Taenia solium is a tapeworm of global importance due to the burden of disease associated with human epilepsy caused by neurocysticercosis. Unfortunately, diagnostic challenges impede control efforts in many low and middle-income countries. This review examines publications concerning Taenia species in the Lao PDR with a focus on T. solium to inform future research and control programmes.

METHODS

PubMed and Scopus databases were primary sources of evidence. Publications must have reported taeniasis or T. solium results from Lao PDR. Publications repeating results or samples were combined into unique projects.

RESULTS

A total of 64 publications were included and summarised into 46 projects. The majority of projects applied faecal microscopy as their only diagnostic technique. As a result, the specific species of Taenia was often not determined. Only five projects used molecular techniques to identify the species observed. Only case report of neurocysticercosis has been published. The northern region was included in half the number of projects compared to the south, despite being a high-risk area T. solium.

CONCLUSIONS

The diagnostic challenge of determining the species of Taenia present in a faecal sample presents a significant limitation to the control of T. solium in Lao PDR and is an experience that is relevant to many other low and middle-income countries. There must be an improved understanding of the distribution and frequency of T. solium if disease control efforts are to be intensified to reduce the burden of neurocysticercosis, as encouraged by WHO and others. It is hoped that this can be achieved through non-biological risk mapping tools and the more frequent application of molecular tools to routine sample collection. Diagnostic tools that are applicable to low resource settings should be a priority area of research for T. solium.

Cotton cultivated area detection and yield monitoring combining remote sensing with field data in lower Indus River basin, Pakistan

As the Earth's population continuously increase with the passage of time, the demand for agricultural raw material for human need increases. It is critical to maintaining updated and accurate information about the dynamics and properties of the world agricultural systems. As cash crop, the updated information of the spatial distribution of cotton field is necessary to monitor the crop area and growth changes at regional level. We used 8-day enhanced vegetation index (EVI) time series to detect cotton crop area and binomial probabilistic approach to obtain the probability distribution of cotton crop occurrence. We used Gaussian kriging to derive cotton yield inside the detected cotton crop areas through crop reporting data. We also used field data from farmers to validate the cotton yield results. A strong correlation between the MODIS-derived cotton cultivated area and statistical data at the tehsil level were achieved (R² = 0.84) for all study years (2004-2019). The total accuracy for the cotton crop area detection was 84.6% and yield prediction was 92.1%. Our study presents new approaches to map cotton area and yield, which are applicable to other regions through machine learning.

Spatial distribution and influencing factors of thyroid cancer hospitalization rate among rural residents in Fujian Province, China from 2012 to 2016

This study aimed to explore the spatial distribution and influencing factors of thyroid cancer hospitalization rates in Fujian Province from 2012 to 2016. Hospitalization reimbursement records for thyroid cancer were obtained from 2025 hospitals in Fujian Province from 2012 to 2016. The Moran's I method was used for spatial autocorrelation analysis and to further draw a spatial cluster map in Fujian. Geographic detectors were used to explore the effect of risk factors on spatial heterogeneity of inpatient service utilization for thyroid cancer. The study showed that there was obvious temporal and spatial heterogeneity in the utilization rate of inpatient services for thyroid cancer in Fujian Province, which were mainly concentrated in Fuzhou, with Lianjiang County as the center, and the gathering area involves 26 counties and cities. Among a variety of environmental factors, air quality index (AQI) (q = 0.481), carbon sequestration (q = 0.161), and carbon emissions (q = 0.155) were the main factors affecting the hospitalization rates. AQI and carbon emissions were generally positively correlated with hospitalization rates, and carbon sequestration was negatively correlated. After the interaction of the two factors, the interpretation of the hospitalization rate was enhanced. The obvious spatial heterogeneity will help the relevant departments to adjust measures to local conditions and allocate medical resources rationally to ease the pressure of seeking medical attention in high-demand areas.

Space—Time Surveillance of COVID-19 Seasonal Clusters: A Case of Sweden

While COVID-19 is a global pandemic, different countries have experienced different morbidity and mortality patterns. We employ retrospective and prospective space–time permutation analysis on COVID-19 positive records across different municipalities in Sweden from March 2020 to February 2021, using data provided by the Swedish Public Health Agency. To the best of our knowledge, this is the first study analyzing nationwide COVID-19 space–time clustering in Sweden, on a season-to-season basis. Our results show that different municipalities within Sweden experienced varying extents of season-dependent COVID-19 clustering in both the spatial and temporal dimensions. The reasons for the observed differences could be related to the differences in the earlier exposures to the virus, the strictness of the social restrictions, testing capabilities and preparedness. By profiling COVID-19 space–time clusters before the introduction of vaccines, this study contributes to public health efforts aimed at containing the virus by providing plausible evidence in evaluating which epidemiologic interventions in the different regions could have worked and what could have not worked.

Spatial epidemiology of highly pathogenic avian influenza subtype H5N6 in Gyeonggi Province, South Korea, 2016-2017

Over four months in the winter of 2016-2017, 343 poultry farms in South Korea reported highly pathogenic avian influenza (HPAI) H5N6 occurrences, leading to the culling of 40 million poultry. Our study aimed to describe the spatial epidemiology of the 2016-2017 HPAI H5N6 outbreak in Gyeonggi Province, the most affected area in South Korea, comprising 35.9% (123) of the HPAI-infected poultry farms, to identify spatial risk factors for the increased probability of HPAI H5N6 occurrence, and to delineate areas with the highest likelihood of infection among different target poultry species. Although the poultry density was risk factor for the all species, rice paddy was only identified as risk factor for chicken and duck farms, not other species farms suggesting different biosecurity measures are required depending on the species. Although spatial effects of HPAI occurrence tended to be clustered within 16 km, the cluster range was reduced to 7 km when considering the identified risk factors, indicating a more geographically focused outbreak response when taking risk factors into account. The areas identified with the highest likelihood of infection can provide evidence, with accessibility to policymakers, to improve risk-based surveillance for HPAI. Our findings provide epidemiological understanding helpful in improving surveillance activity and assisting in the design of more cost-effective intervention policies related to future HPAI outbreaks in South Korea. This article is protected by copyright. All rights reserved.

Serological Survey of Canine Vector-Borne Infections in North-Center Spain

Various factors are currently causing an increase in vector-borne parasitic diseases at a global scale; among them, some stand out, such as climatic disturbances derived from global change, the increase in movements of reservoir animals, or changes in land made by human activity. In the European continent, there have been an increasing number of epidemiological studies focused on the detection of these diseases, especially in dogs. In Spain, there are few epidemiological studies focused on the evaluation of the biotic and abiotic factors that may influence the distribution, such as climatic zones, orography, or presence of water reservoirs. The aim of this study was to analyze the prevalence and distribution of several canine vector-borne diseases caused by Dirofilaria immitis, Leishmania infantum, Anaplasma platys, and Ehrlichia canis in the autonomous community of Castilla y León, the largest region of the Iberian Peninsula, providing a geospatial approach based on a geographic information system (GIS) analysis. Blood from a total of 1,475 domestic dogs from the nine provinces of Castilla y León were analyzed. Also, a GIS analysis of the sample locations was carried out, taking into account the most important predictor variables. The prevalence in dogs infected by D. immitis was 7.19%, and the seroprevalence by L. infantum was 4.61 and 1.56% for A. platys and E. canis. Most of the infected animals were located in areas with stagnant water, irrigated agriculture, or riverbanks, always close to forest and woodland vegetation. These results indicate that dogs living in Castilla y León should take prophylactic measures to avoid infections.

Epidemiological Factors Associated With Caligus rogercresseyi Infection, Abundance, and Spatial Distribution in Southern Chile

Sea lice (Caligus rogercresseyi) are external parasites that affect farmed salmonids in Chile, and the scale of their sanitary and economic impact cannot be overstated. Even though space–time patterns suppose parasite aggregation, specific locations related to different infestation levels, as well as their associated factors across the geographic range involved, had not been investigated as of the writing of the present article. The understanding of the effects and factors entailed by the presence of C. rogercresseyi may be deemed a key element of Integrated Pest Management (IPM). In the present study, the multivariate spatial scan statistic was used to identify geographic areas and times of C. rogercresseyi infestation and to estimate the factors associated with such patterns. We used official C. rogercresseyi monitoring data at the farm level, with a set of 13 covariates, to provide adjustment within the analyses. The analyses were carried out for a period of 5 years (2012–2016), and they included three fish species (Salmo salar, Oncorhynchus mykiss, and Oncorhynchus kisutch) in order to assess the consistency of the identified clusters. A retrospective multinomial, spatial, and temporal scan test was implemented to identify farm clusters of either of the different categories of C. rogercresseyi infested farms: baseline, medium, and high, based on the control chemical threshold established by the health authority. The baseline represents adequate farm performance against C. rogercresseyi infestation. Then, production and environmental factors of the medium and high infestation farms were compared with the baseline using regression techniques. The results revealed a total of 26 clusters (p < 0.001), of which 12 correspond to baseline, 1 to medium, and the remaining 13 to high infestation clusters. In general, baseline clusters are detected in a latitudinal gradient on estuarine areas, with increasing relative risks to complex island water systems. There is a spatial structure in specific sites, north of Los Lagos Region and central Aysén Region, with high infestation clusters and epidemic peaks during 2013. In addition, average weight, salmon species, chemotherapeutants, latitude, temperature, salinity, and year category are factors associated with these C. rogercresseyi patterns. Recommendations for an IPM plan are provided, along with a discussion that considers the involvement of stock density thresholds by salmon species and the spatial structure of the efficacy of chemical control, both intended to avoid the advance of resistance and to minimize environmental residues.

Spatial Dynamics of Two Host-Parasite Relationships on Intertidal Oyster Reefs

Intertidal reefs comprised of the eastern oyster (Crassostrea virginica) have long experienced habitat loss, altering habitat patch characteristics of size and distance from edge to interior, potentially influencing spatial dynamics of host-parasite relationships. Using two parasitic relationships, one between eastern oyster host and parasitic oyster pea crab (Zaops ostreum) and the other between a xanthid crab (Eurypanopeus depressus) and a parasitic rhizocephalan barnacle (Loxothylacus panopaei), we examined how host-parasite population characteristics varied on intertidal reefs by season, reef size, and distance from edge to interior. Pea crab prevalence was more related to habitat characteristics rather than host density, as pea crab prevalence was the highest on large reefs and along edges, areas of comparatively lower oyster densities. Reef size did not influence densities of parasitized or non-parasitized xanthid crabs, but densities varied from edge to interior. Non-parasitized xanthids had significantly lower densities along the reef edge compared to more interior reef locations, while parasitized xanthid crabs had no significant edge to interior pattern. Organismal size had a varied relationship based upon habitat characteristics, as pea crab carapace width (CW) varied interactively with season and reef size, whereas CW of parasitized/non-parasitized xanthid crabs varied significantly between edge and interior locations. These results demonstrated that influential habitat characteristics, such as patch size and edge versus interior, are both highly species and host-parasite specific. Therefore, continued habitat alteration and fragmentation of critical marine habitats may further impact spatial dynamics of host-parasite relationships.

Molecular approaches reveal weak sibship aggregation and a high dispersal propensity in a non-native fish parasite

Inferring parameters related to the aggregation pattern of parasites and to their dispersal propensity are important for predicting their ecological consequences and evolutionary potential. Nonetheless, it is notoriously difficult to infer these parameters from wildlife parasites given the difficulty in tracking these organisms. Molecular-based inferences constitute a promising approach that has yet rarely been applied in the wild. Here, we combined several population genetic analyses including sibship reconstruction to document the genetic structure, patterns of sibship aggregation, and the dispersal dynamics of a non-native parasite of fish, the freshwater copepod ectoparasite Tracheliastes polycolpus. We collected parasites according to a hierarchical sampling design, with the sampling of all parasites from all host individuals captured in eight sites spread along an upstream-downstream river gradient. Individual multilocus genotypes were obtained from 14 microsatellite markers, and used to assign parasites to full-sib families and to investigate the genetic structure of T. polycolpus among both hosts and sampling sites. The distribution of full-sibs obtained among the sampling sites was used to estimate individual dispersal distances within families. Our results showed that T. polycolpus sibs tend to be aggregated within sites but not within host individuals. We detected important upstream-to-downstream dispersal events of T. polycolpus between sites (modal distance: 25.4 km; 95% CI [22.9, 27.7]), becoming scarcer as the geographic distance from their family core location increases. Such a dispersal pattern likely contributes to the strong isolation-by-distance observed at the river scale. We also detected some downstream-to-upstream dispersal events (modal distance: 2.6 km; 95% CI [2.2-23.3]) that likely result from movements of infected hosts. Within each site, the dispersal of free-living infective larvae among hosts likely contributes to increasing genetic diversity on hosts, possibly fostering the evolutionary potential of T. polycolpus.

Angiostrongylus vasorum in Domestic Dogs in Castilla y León, Iberian Peninsula, Spain

Simple Summary

Canine angiostrongylosis is a vascular and pulmonary disease caused by Angiostrongylus vasorum. In Europe, there has been an increasing number of studies showing a rise in the studies in both domestic and wild canids. In Spain, angiostrongylosis is still little-known, and studies are scarce. The aim of this study was to analyze the presence of A. vasorum in 1475 domestic dogs from the autonomous region of Castilla y León (Spain). Antigens of this species were found in 0.75% of the tested dogs, most of which lived outdoors, a significant risk factor. The geographic information system (GIS) analysis showed that the infected animals mainly lived in areas with mild temperatures and climate during most of the year and close to water bodies: stagnant water; riverbanks or irrigated areas with a predominance of alder, holm oak and gall oak forests. One main conclusion was the need to carry out more studies in countries and areas with the presence of this parasite in order to know the prevalence in dogs and wild canids, as well as determine the environmental factors that influence its presence, to be able to take more effective measures to control this disease.

Abstract

Angiostrongylus vasorum is the causative agent of canine angiostrongylosis, a disease affecting domestic and wild canids. In Europe, it is an emerging disease, mainly reported in red foxes. In Spain, there are a few studies that address the prevalence and pathology of this disease. Castilla y León is the largest region of the Iberian Peninsula, whose extensive area is 94,224 km²; however, until now, there have been no epidemiological studies on this disease. Therefore, the aim of this study was to analyze the presence of antigens of A. vasorum in 1475 dogs from Castilla y León, showing an overall prevalence of 0.75%. The infected dogs were mainly outdoors, guard and hunting breed dogs and living in locations with mild climates close to areas of high edaphic humidity, such as stagnant water, irrigated crops or riverbanks, with the vegetation dominated by alders, holm oak and gall oak forests, where the intermediate hosts develop. It is necessary to carry out more in-depth studies on the epidemiology and pathology of this disease in Spain and Europe in order to carry out efficient control in both domestic and wild animals.

Prevalence of tick-transmitted pathogens in cattle reveals that Theileria parva, Babesia bigemina and Anaplasma marginale are endemic in Burundi

BACKGROUND

Tick-borne diseases (TBDs) constitute a major constraint for livestock development in sub-Saharan Africa, with East Coast fever (ECF) being the most devastating TBD of cattle. However, in Burundi, detailed information is lacking on the current prevalence of TBDs and on the associated economic losses from mortality and morbidity in cattle as well as the costs associated with TBD control and treatment. The aim of this study was, therefore, to assess the prevalence and spatial distribution of tick-borne pathogens (TBPs) in cattle across the major agro-ecological zones (AEZs) in Burundi.

METHODS

In a cross-sectional study conducted in ten communes spanning the five main AEZs in Burundi, blood samples were taken from 828 cattle from 305 farms between October and December 2017. Evidence of Theileria parva infection was assessed by antibody level, measured using a polymorphic immunodominant molecule (PIM) antigen-based enzyme-linked immunosorbent assay (ELISA) and by a T. parva-specific p104 gene-based nested PCR. Antibodies against Theileria mutans infection were detected using the 32-kDa antigen-based indirect ELISA, while the 200-kDa antigen and the major surface protein 5 (MSP5)-based indirect ELISA were used to detect antibodies against Babesia bigemina and Anaplasma marginale, respectively.

RESULTS

The prevalence of T. parva across the ten communes sampled ranged from 77.5 to 93.1% and from 67.8 to 90.0% based on the ELISA and PCR analysis, respectively. A statistically significant difference in infection was observed between calves and adult cattle; however, T. parva infection levels were not significantly associated with sex and breed. The seroprevalence indicating exposure to T. mutans, B. bigemina and A. marginale ranged from 30 to 92.1%, 33.7 to 90% and 50 to 96.2%, respectively. Mixed infections of TBPs were detected in 82.91% of cattle sampled, with 11 different combinations of pathogen species detected .

CONCLUSIONS

The findings indicate that T. parva, A. marginale and B. bigemina infections are endemic in Burundi. Knowledge of the spatial distribution of TBPs will facilitate the design of effective targeted strategies to control these diseases. There is a need for further investigations of the distribution of tick vectors and the population structure of TBPs in order to identify the key epidemiological factors contributing to TBD outbreaks in Burundi.

Negative density-dependent parasitism in a group-living carnivore

Animals living at high population densities commonly experience greater exposure to disease, leading to increased parasite burdens. However, social animals can benefit immunologically and hygienically from cooperation, and individuals may alter their socio-spatial behaviour in response to infection, both of which could counteract density-related increases in exposure. Consequently, the costs and benefits of sociality for disease are often uncertain. Here, we use a long-term study of a wild European badger population (Meles meles) to investigate how within-population variation in host density determines infection with multiple parasites. Four out of five parasite taxa exhibited consistent spatial hotspots of infection, which peaked among badgers living in areas of low local population density. Combined movement, survival, spatial and social network analyses revealed that parasite avoidance was the likely cause of this negative density dependence, with possible roles for localized mortality, encounter-dilution effects, and micronutrient-enhanced immunity. These findings demonstrate that animals can organize their societies in space to minimize parasite infection, with important implications for badger behavioural ecology and for the control of badger-associated diseases.

Statistical methods for linking geostatistical maps and transmission models: Application to lymphatic filariasis in East Africa

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Novel methodology for combining geostatistical mapping and transmission modelling.

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Guide the planning of spatial control programmes by identifying affected areas.

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Current intervention strategy will not be sufficient to eliminate LF in most areas.

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Alternative strategies will be required to accelerate LF elimination in East Africa.

Infectious diseases remain one of the major causes of human mortality and suffering. Mathematical models have been established as an important tool for capturing the features that drive the spread of the disease, predicting the progression of an epidemic and hence guiding the development of strategies to control it. Another important area of epidemiological interest is the development of geostatistical methods for the analysis of data from spatially referenced prevalence surveys. Maps of prevalence are useful, not only for enabling a more precise disease risk stratification, but also for guiding the planning of more reliable spatial control programmes by identifying affected areas. Despite the methodological advances that have been made in each area independently, efforts to link transmission models and geostatistical maps have been limited. Motivated by this fact, we developed a Bayesian approach that combines fine-scale geostatistical maps of disease prevalence with transmission models to provide quantitative, spatially-explicit projections of the current and future impact of control programs against a disease. These estimates can then be used at a local level to identify the effectiveness of suggested intervention schemes and allow investigation of alternative strategies. The methodology has been applied to lymphatic filariasis in East Africa to provide estimates of the impact of different intervention strategies against the disease.

Variation in Anopheles distribution and predictors of malaria infection risk across regions of Madagascar

BACKGROUND

Deforestation and land use change is widespread in Madagascar, altering local ecosystems and creating opportunities for disease vectors, such as the Anopheles mosquito, to proliferate and more easily reach vulnerable, rural populations. Knowledge of risk factors associated with malaria infections is growing globally, but these associations remain understudied across Madagascar's diverse ecosystems experiencing rapid environmental change. This study aims to uncover socioeconomic, demographic, and ecological risk factors for malaria infection across regions through analysis of a large, cross-sectional dataset.

METHODS

The objectives were to assess (1) the ecological correlates of malaria vector breeding through larval surveys, and (2) the socioeconomic, demographic, and ecological risk factors for malaria infection in four ecologically distinct regions of rural Madagascar. Risk factors were determined using multilevel models for the four regions included in the study.

RESULTS

The presence of aquatic agriculture (both within and surrounding communities) is the strongest predictive factor of habitats containing Anopheles larvae across all regions. Ecological and socioeconomic risk factors for malaria infection vary dramatically across study regions and range in their complexity.

CONCLUSIONS

Risk factors for malaria transmission differ dramatically across regions of Madagascar. These results may help stratifying current malaria control efforts in Madagascar beyond the scope of existing interventions.

Prevalence, molecular epidemiology and zoonotic risk of Entamoeba spp. from experimental macaques in Yunnan Province, southwestern China

Amebiasis is a worldwide parasitic zoonosis, with symptoms of abdominal discomfort, indigestion, diarrhea, and even death. However, limited information about the prevalence of Entamoeba spp. in experimental nonhuman primates (NHPs) in southwestern China is available. The objective of the current study was to investigate the frequency and species identity of Entamoeba to evaluate potential zoonotic risk factors for Entamoeba spp. infection in experimental NHPs. A total of 505 fecal samples were collected from NHPs (macaques) and analyzed by PCR analysis the small subunit rRNA (SSU rRNA) gene of Entamoeba spp. Forty-seven specimens were positive for Entamoeba spp., and the prevalence of Entamoeba spp. was 9.31% (47/505). Significant differences in the prevalence rates among the three breeds (P = 0.002 < 0.01, df = 2, χ² = 12.33) and feed types (P = 0.001 < 0.01, df = 1, χ² = 10.12) were observed. Altogether, four Entamoeba species, including E. dispar (57.44%), E. chattoni (29.78%), E. histolytica (6.38%), and E. coli (6.38%), were identified by DNA sequence analysis. The results suggested a low prevalence but high diversity of Entamoeba species in experimental NHPs in Yunnan Province, southwestern China. Results of this study contribute to the knowledge of the genetic characteristics of Entamoeba spp. in NHPs.

Comparing spatio-temporal distribution of the most common human parasitic infections in Iran over two periods 2007 to 2012 and 2013 to 2018: A systematic quantitative literature review

This study analyses the spatio-temporal trend of the prevalence of the four most prevalent parasitic diseases in Iran over two periods, 2007 to 2012 and 2013 to 2018, indicating high-risk and low-risk areas. Out of 19 126 articles, we selected 220 articles for data extraction and calculated the pooled prevalence for cutaneous leishmaniasis, human toxoplasmosis, giardiasis and blastocystosis for all 31 provinces in the country. Anselin local Moran's I was used to identify clusters and outliers in the prevalence rates. The mean prevalence of cutaneous leishmaniasis patients was found 35.12 per 100 000 in 2007 to 2012 but fell to 19.12 per 100 000 in the 2013 to 2018 period. The mean prevalence of acute and chronic toxoplasmosis was 2.36% and 32.5%, respectively, in 2007 to 2012, which changed to 2.28% and 31.14% in 2013 to 2018. The total prevalence of giardiasis declined from 9.8% in 2007 to 2012 to 4.8% in 2013 to 2018, while the mean prevalence of blastocystosis declined from 8.9% in 2007 to 2012 to 6.76% in the 2013 to 2018 period. There was only one high-high cluster in 2007 to 2012 and that was due to giardiasis, while there were two in 2013 to 2018, one for blastocystosis and one for chronic toxoplasmosis. The total prevalence of blastocystosis, giardiasis and cutaneous leishmaniasis in Iran has continually declined since 2007. In contrast, the prevalence of toxoplasmosis in pregnant Iranian women has not been changed. Iran's Midwest has more parasitic infections compared to the Mideast, which may be explained by the existence of vast deserts and consequently dry and hot climate in the latter part of the country.

The typical cestodes of the red fox in eastern areas of the Iberian Peninsula have a grouped distribution

The red fox (Vulpes vulpes) is the most abundant wild canid in the Iberian Peninsula, and can act as a carrier of a wide range of parasite species shared with dogs and cats and which are sometimes zoonoses. Despite this, few studies are available describing the distribution and epidemiology of the cestode community of this opportunistic carnivore in areas of Mediterranean climate. In this study, prevalence, intensity, abundance and aggregation coefficient of cestodes found in 286 red foxes of the Valencian Community (East Spain) were calculated. For the most prevalent species, presence data were combined with environmental variables in order to build spatial models and predict the limiting factors associated with the decrease of suitable habitat for these parasites. The overall prevalence of cestodes was 83.22 % (238/286). Specifically, foxes harboured Mesocestoides spp. (75.87 %), Joyeuxiella echinorhynchoides (27.62 %), Taenia pisiformis (13.29 %), Dypilidium caninum (3.15 %), Taenia polyacantha (1.05 %), Taenia hydatigena (0.70 %), Taenia crassiceps (0.70 %) and Taenia spp. (0.35 %). Tetrathyridia larvae were found both in thoracic and abdominal cavity of three foxes (1.05 %), being the first time that this metacestode stage is described in the thoracic cavity of the red fox. Models on Mesocestoides spp. (Area Under the Curve, AUC = 0.80) and J. echinorhynchoides (AUC = 0.83) indicate that anthropogenic, climatic and environmental factors efficiently describe the habitat shape of parasites. This study emphasizes that foxes in Mediterranean areas are hosts of cestodes of veterinary and public health concern. Furthermore, our results demonstrate the usefulness of Ecological Niche Modeling applications for mapping the distribution of fox parasites and identifying areas of higher epidemiological risk for this wild canid, as well as for dogs and cats and, in the case of Mesocestoides spp., for humans.

Macroimmunology: The drivers and consequences of spatial patterns in wildlife immune defence

The prevalence and intensity of parasites in wild hosts varies across space and is a key determinant of infection risk in humans, domestic animals and threatened wildlife. Because the immune system serves as the primary barrier to infection, replication and transmission following exposure, we here consider the environmental drivers of immunity. Spatial variation in parasite pressure, abiotic and biotic conditions, and anthropogenic factors can all shape immunity across spatial scales. Identifying the most important spatial drivers of immunity could help pre-empt infectious disease risks, especially in the context of how large-scale factors such as urbanization affect defence by changing environmental conditions. We provide a synthesis of how to apply macroecological approaches to the study of ecoimmunology (i.e. macroimmunology). We first review spatial factors that could generate spatial variation in defence, highlighting the need for large-scale studies that can differentiate competing environmental predictors of immunity and detailing contexts where this approach might be favoured over small-scale experimental studies. We next conduct a systematic review of the literature to assess the frequency of spatial studies and to classify them according to taxa, immune measures, spatial replication and extent, and statistical methods. We review 210 ecoimmunology studies sampling multiple host populations. We show that whereas spatial approaches are relatively common, spatial replication is generally low and unlikely to provide sufficient environmental variation or power to differentiate competing spatial hypotheses. We also highlight statistical biases in macroimmunology, in that few studies characterize and account for spatial dependence statistically, potentially affecting inferences for the relationships between environmental conditions and immune defence. We use these findings to describe tools from geostatistics and spatial modelling that can improve inference about the associations between environmental and immunological variation. In particular, we emphasize exploratory tools that can guide spatial sampling and highlight the need for greater use of mixed-effects models that account for spatial variability while also allowing researchers to account for both individual- and habitat-level covariates. We finally discuss future research priorities for macroimmunology, including focusing on latitudinal gradients, range expansions and urbanization as being especially amenable to large-scale spatial approaches. Methodologically, we highlight critical opportunities posed by assessing spatial variation in host tolerance, using metagenomics to quantify spatial variation in parasite pressure, coupling large-scale field studies with small-scale field experiments and longitudinal approaches, and applying statistical tools from macroecology and meta-analysis to identify generalizable spatial patterns. Such work will facilitate scaling ecoimmunology from individual- to habitat-level insights about the drivers of immune defence and help predict where environmental change may most alter infectious disease risk.

The problem of scale in the prediction and management of pathogen spillover

Disease emergence events, epidemics and pandemics all underscore the need to predict zoonotic pathogen spillover. Because cross-species transmission is inherently hierarchical, involving processes that occur at varying levels of biological organization, such predictive efforts can be complicated by the many scales and vastness of data potentially required for forecasting. A wide range of approaches are currently used to forecast spillover risk (e.g. macroecology, pathogen discovery, surveillance of human populations, among others), each of which is bound within particular phylogenetic, spatial and temporal scales of prediction. Here, we contextualize these diverse approaches within their forecasting goals and resulting scales of prediction to illustrate critical areas of conceptual and pragmatic overlap. Specifically, we focus on an ecological perspective to envision a research pipeline that connects these different scales of data and predictions from the aims of discovery to intervention. Pathogen discovery and predictions focused at the phylogenetic scale can first provide coarse and pattern-based guidance for which reservoirs, vectors and pathogens are likely to be involved in spillover, thereby narrowing surveillance targets and where such efforts should be conducted. Next, these predictions can be followed with ecologically driven spatio-temporal studies of reservoirs and vectors to quantify spatio-temporal fluctuations in infection and to mechanistically understand how pathogens circulate and are transmitted to humans. This approach can also help identify general regions and periods for which spillover is most likely. We illustrate this point by highlighting several case studies where long-term, ecologically focused studies (e.g. Lyme disease in the northeast USA, Hendra virus in eastern Australia, Plasmodium knowlesi in Southeast Asia) have facilitated predicting spillover in space and time and facilitated the design of possible intervention strategies. Such studies can in turn help narrow human surveillance efforts and help refine and improve future large-scale, phylogenetic predictions. We conclude by discussing how greater integration and exchange between data and predictions generated across these varying scales could ultimately help generate more actionable forecasts and interventions. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.

Malaria Hotspots: Is There Epidemiological Evidence for Fine-Scale Spatial Targeting of Interventions?

As data at progressively granular spatial scales become available, the temptation is to target interventions to areas with higher malaria transmission - so-called hotspots - with the aim of reducing transmission in the wider community. This paper reviews literature to determine if hotspots are an intrinsic feature of malaria epidemiology and whether current evidence supports hotspot-targeted interventions. Hotspots are a consistent feature of malaria transmission at all endemicities. The smallest spatial unit capable of supporting transmission is the household, where peri-domestic transmission occurs. Whilst the value of focusing interventions to high-burden areas is evident, there is currently limited evidence that local-scale hotspots fuel transmission. As boundaries are often uncertain, there is no conclusive evidence that hotspot-targeted interventions accelerate malaria elimination.

Analysis of serological data to investigate heterogeneity of malaria transmission: a community-based cross-sectional study in an area conducting elimination in Indonesia

Background

Analysis of anti-malarial antibody responses has the potential to improve characterization of the variation in exposure to infection in low transmission settings, where conventional measures, such as entomological estimates and parasitaemia point prevalence become less sensitive and expensive to measure. This study evaluates the use of sero-epidemiological analysis to investigate heterogeneity of transmission in area conducting elimination in Indonesia.

Methods

Filter paper bloodspots and epidemiological data were collected through a community-based cross-sectional study conducted in two sub-districts in Sabang municipality, Aceh province, Indonesia in 2013. Antibody responses to merozoite surface protein 1 (MSP-1₁₉) and apical membrane antigen 1 (AMA-1) for Plasmodium falciparum and Plasmodium vivax were measured using indirect enzyme-linked immunosorbent assay (ELISA). Seroconversion rates (SCR) were estimated by fitting a simple reversible catalytic model to seroprevalence data for each antibody. Spatial analysis was performed using a Normal model (SaTScan v.9.4.2) to identify the clustering of higher values of household antibody responses. Multiple logistic regression was used to investigate factors associated with exposure.

Results

1624 samples were collected from 605 households. Seroprevalence to any P. falciparum antigen was higher than to any P. vivax antigen, 6.9% (95% CI 5.8–8.2) vs 2.0% (95% CI 1.4–2.8). SCR estimates suggest that there was a significant change in P. falciparum transmission with no exposure seen in children under 5 years old. Plasmodium falciparum SCR in over 5 years old was 0.008 (95% CI 0.003–0.017) and 0.012 (95% CI 0.005–0.030) in Sukakarya and Sukajaya sub-districts, respectively. Clusters of exposure were detected for both P. falciparum and P. vivax, most of them in Sukajaya sub-district. Higher age, P. vivax seropositivity and use of long-lasting insecticide-treated bed net (LLIN) were associated with higher P. falciparum exposure.

Conclusion

Analysis of community-based serological data helps describe the level of transmission, heterogeneity and factors associated with malaria transmission in Sabang. This approach could be an important additional tool for malaria monitoring and surveillance in low transmission settings in Indonesia.

Electronic supplementary material

The online version of this article (10.1186/s12936-019-2866-z) contains supplementary material, which is available to authorized users.

Kernel-density estimation and approximate Bayesian computation for flexible epidemiological model fitting in Python

Fitting complex models to epidemiological data is a challenging problem: methodologies can be inaccessible to all but specialists, there may be challenges in adequately describing uncertainty in model fitting, the complex models may take a long time to run, and it can be difficult to fully capture the heterogeneity in the data. We develop an adaptive approximate Bayesian computation scheme to fit a variety of epidemiologically relevant data with minimal hyper-parameter tuning by using an adaptive tolerance scheme. We implement a novel kernel density estimation scheme to capture both dispersed and multi-dimensional data, and directly compare this technique to standard Bayesian approaches. We then apply the procedure to a complex individual-based simulation of lymphatic filariasis, a human parasitic disease. The procedure and examples are released alongside this article as an open access library, with examples to aid researchers to rapidly fit models to data. This demonstrates that an adaptive ABC scheme with a general summary and distance metric is capable of performing model fitting for a variety of epidemiological data. It also does not require significant theoretical background to use and can be made accessible to the diverse epidemiological research community.

Spatial overlaps in the distribution of HIV/AIDS and malaria in Zimbabwe

BACKGROUND

In most developing economies particularly in Africa, more people are likely to die of HIV/AIDS and malaria compared to other diseases. HIV/AIDS tends to be superimposed on the long standing malaria burden particularly in sub-Saharan Africa. The detection and understanding of spatial overlaps in disease occurrence is important for integrated and targeted disease control. Integrated disease control can enhance efficiency and cost-effectiveness through the development of drugs targeting multiple infections in the same geographic space.

METHODS

Using Zimbabwe as a case study, this study tests the hypothesis that malaria clusters coincide with HIV/AIDS clusters in space. Case data for the two diseases were obtained from the Ministry of Health and Child Care in Zimbabwe at district level via the District Health Information System (DHIS). Kulldorff's spatial scan statistic was used to test for spatial overlaps in clusters of high cases of HIV/AIDS and malaria at district level. The spatial scan test was used to identify areas with higher cases of HIV/AIDS and malaria than would be expected under spatial randomness.

RESULTS

Results of this study indicate that primary clusters of HIV/AIDS and malaria were not spatially coincident in Zimbabwe. While no spatial overlaps were detected between primary clusters of the two diseases, spatial overlaps were detected among statistically significant secondary clusters of HIV/AIDS and malaria. Spatial overlaps between HIV/AIDS and malaria occurred in five districts in the northern and eastern regions of Zimbabwe. In addition, findings of this study indicate that HIV/AIDS is more widespread in Zimbabwe compared to malaria.

CONCLUSIONS

The results of this study may therefore be used as a basis for spatially-targeted control of HIV/AIDS and malaria particularly in high disease burden areas. This is important as previous interventions have targeted the two diseases separately. Thus, targeted control could assist in resource allocation through prioritising areas in greatest need hence maximising the impact of disease control.

Parasitic infections in relation to practices and knowledge in a rural village in Northern Thailand with emphasis on fish-borne trematode infection

The present study integrates several aspects of a parasitological survey in a rural community village combining community knowledge of parasites, their potential transmission routes and health risk factors. A rural community located in Northern Thailand was surveyed for intestinal parasites, and an overall prevalence of 45.2% for helminths and 4.8% for protozoan infections was identified. Socio-demographic characteristics, customs and perceptions were compiled using individual questionnaires and interviews for participants surveyed for parasitic screening. The results allowed us to determine the knowledge and perception of local people concerning helminthic infection and transmission. Despite the fact that the participants in this community were aware of parasitic transmission routes, their widespread custom of eating raw fish and meat render the reduction of helminthiasis difficult. A detailed study on the infection of fish-borne parasitic trematodes, the most prevalent helminth, allowed us to determine that the distance from a given household to the river is a determinant of infection intensity. Health education activities organised in the local community resulted in a change in perception of risks associated with parasite transmission.

Parasites and Host Species Barriers in Animal Hybrid Zones

Species barriers are tested in hybrid zones when gene flow occurs between hybridizing species. Hybridization can erode species barriers, lead to the introgression of adaptive traits, or remain stable through time. Outcomes in hybrid zones are influenced by divergence between the hybridizing taxa, behavior, ecology, and geography. Parasites and pathogens play a major role in host fitness and appear to have varied impacts on species barriers in hybrid zones. We comprehensively reviewed the literature on parasitism in animal hybrid zones and present an evolutionary framework within which to consider parasite-hybrid interactions. Parasites most frequently show potential to contribute to species barrier breakdown in hybrid zones, but also frequently show potential to facilitate the maintenance of species barriers. Incorporating eco-immunology, parasite community theory, and spatiotemporal approaches will be important as genomic tools allow researchers to examine parasites and hybrid zones at greater resolution and in a diversity of natural habitats.

Mapping influenza activity in emergency departments in France using Bayesian model-based geostatistics

BACKGROUND

Maps of influenza activity are important tools to monitor influenza epidemics and inform policymakers. In France, the availability of a high-quality data set from the Oscour^® surveillance network, covering 92% of hospital emergency department (ED) visits, offers new opportunities for disease mapping. Traditional geostatistical mapping methods such as Kriging ignore underlying population sizes, are not suited to non-Gaussian data and do not account for uncertainty in parameter estimates.

OBJECTIVE

Our objective was to create reliable weekly interpolated maps of influenza activity in the ED setting, to inform Santé publique France (the French national public health agency) and local healthcare authorities.

METHODS

We used Oscour^® data of ED visits covering the 2016-2017 influenza season. We developed a Bayesian model-based geostatistical approach, a class of generalized linear mixed models, with a multivariate normal random field as a spatially autocorrelated random effect. Using R-INLA, we developed an algorithm to create maps of the proportion of influenza-coded cases among all coded visits. We compared our results with maps obtained by Kriging.

RESULTS

Over the study period, 45 565 (0.82%) visits were coded as influenza cases. Maps resulting from the model are presented for each week, displaying the posterior mean of the influenza proportion and its associated uncertainty. Our model performed better than Kriging.

CONCLUSIONS

Our model allows producing smoothed maps where the random noise has been properly removed to reveal the spatial risk surface. The algorithm was incorporated into the national surveillance system to produce maps in real time and could be applied to other diseases.

Mapping the stability of malaria hotspots in Bangladesh from 2013 to 2016

BACKGROUND

Malaria claims hundreds of thousands of lives each year, most of them children. A "malaria-free world" is the World Health Organization's vision, but elimination from the southeast Asian Region is hampered by factors including anti-malarial resistance and systematic underreporting. Malaria is a significant public health problem in Bangladesh and while there have been recent gains in control, there is large spatial and temporal heterogeneity in the disease burden. This study aims to determine the pattern and stability of malaria hotspots in Bangladesh with the end goal of informing intervention planning for elimination.

RESULTS

Malaria in Bangladesh exhibited highly seasonal, hypoendemic transmission in geographic hotspots, which remained conserved over time. The southeast areas of the Chittagong Hill Tracts were identified as malaria hotspots for all 4 years examined. Similarly, areas in Sunamganj and Netrakona districts in the Northeast were hotspots for 2013-2016. Highly stable hotspots from 1 year predicted the following year's hotspot locations in the southeast of Bangladesh. Hotspots did not appear to act as sources of spread with no evidence of consistent patterns of contiguous spread or recession of hotspots as high or low transmission seasons progressed.

CONCLUSIONS

Areas were identified with temporal and spatial clustering of high malaria incidence in Bangladesh. Further studies are required to understand the vector, sociodemographic and disease dynamics within these hotspots. Given the low caseloads occurring in the low transmission seasons, and the conserved nature of malaria hotspots, directing resources towards these areas may be an efficient way to achieve malaria elimination in Bangladesh.

Neglected Tropical Disease Control - The Case for Adaptive, Location-specific Solutions

The world is experiencing environmental and social change at an unprecedented rate, with the effects being felt at local, regional, and international scales. This phenomenon may disrupt interventions against neglected tropical diseases (NTDs) that operate on the basis of linear scaling and 'one-size-fits-all'. Here we argue that investment in field-based data collection and building modelling capacity is required; that it is important to consider unintended consequences of interventions; that inferences can be drawn from wildlife ecology; and that interventions should become more location-specific. Collectively, these ideas underpin the development of adaptive decision-support tools that are sufficiently flexible to address emerging issues within the Anthropocene.

Spatiotemporal distribution and population at risk of soil-transmitted helminth infections following an eight-year school-based deworming programme in Burundi, 2007-2014

Background

Investigating the effect of successive annual deworming rounds on the spatiotemporal distribution of infection prevalence and numbers at risk for soil-transmitted helminths (STHs) can help identify communities nearing elimination and those needing further interventions. In this study, we aim to quantify the impact of an 8-year mass drug administration (MDA) programme (from 2007 to 2014) on the spatiotemporal distribution of prevalence of STH infections and to estimate the number of school-aged children infected with STHs in Burundi.

Methods

During annual longitudinal school-based surveys in Burundi between 2007 and 2011, STH infection and anthropometric data for a total of 40,656 children were collected; these data were supplemented with data from a national survey conducted in 2014. Bayesian model based geostatistics (MBG) were used to generate predictive prevalence maps for each STH species and year. The numbers of children at-risk of infection per district between 2008 and 2014 were estimated as the product of the predictive prevalence maps and population density maps.

Results

Overall, the degree of spatial clustering of STH infections decreased between 2008 and 2011; in 2014 the geographical clusters of all STH infections reappeared. The reduction in prevalence was small for Ascaris lumbricoides and Trichuris trichiura in the centre and central north of the country. Our predictive prevalence maps for hookworm indicate a reduction in prevalence along the periphery of the country. The predicted number of children infected with any STH species decreased substantially between 2007 and 2011, but in 2014 there was an increase in the predicted number of children infected with A. lumbricoides and T. trichiura. In 2014, the districts with the highest predicted number of children infected with A. lumbricoides, T. trichiura and hookworms were Kibuye district (n = 128,903), Mabayi district (n = 35,302) and Kiremba (n = 87,511), respectively.

Conclusions

While the MDA programme in Burundi resulted in a reduction in STH prevalence, this reduction was spatiotemporally heterogeneous, with some pockets of high prevalence remaining, suggesting that treatment coverage and complementary interventions should be evaluated to improve impact.

Electronic supplementary material

The online version of this article (10.1186/s13071-017-2505-x) contains supplementary material, which is available to authorized users.

Effect of transmission intensity on hotspots and micro-epidemiology of malaria in sub-Saharan Africa

BACKGROUND

Malaria transmission intensity is heterogeneous, complicating the implementation of malaria control interventions. We provide a description of the spatial micro-epidemiology of symptomatic malaria and asymptomatic parasitaemia in multiple sites.

METHODS

We assembled data from 19 studies conducted between 1996 and 2015 in seven countries of sub-Saharan Africa with homestead-level geospatial data. Data from each site were used to quantify spatial autocorrelation and examine the temporal stability of hotspots. Parameters from these analyses were examined to identify trends over varying transmission intensity.

RESULTS

Significant hotspots of malaria transmission were observed in most years and sites. The risk ratios of malaria within hotspots were highest at low malaria positive fractions (MPFs) and decreased with increasing MPF (p < 0.001). However, statistical significance of hotspots was lowest at extremely low and extremely high MPFs, with a peak in statistical significance at an MPF of ~0.3. In four sites with longitudinal data we noted temporal instability and variable negative correlations between MPF and average age of symptomatic malaria across all sites, suggesting varying degrees of temporal stability.

CONCLUSIONS

We observed geographical micro-variation in malaria transmission at sites with a variety of transmission intensities across sub-Saharan Africa. Hotspots are marked at lower transmission intensity, but it becomes difficult to show statistical significance when cases are sparse at very low transmission intensity. Given the predictability with which hotspots occur as transmission intensity falls, malaria control programmes should have a low threshold for responding to apparent clustering of cases.

An integrated study of human and animal infectious disease in the Lake Victoria crescent small-holder crop-livestock production system, Kenya

BACKGROUND

The neglected zoonotic diseases (NZD) are an understudied group that are a major cause of illness throughout the developing world. In general, little is known about the prevalence and burden of NZDs in affected communities, particularly in relation to other infectious diseases with which they are often co-endemic. We describe the design and descriptive epidemiological outputs from an integrated study of human and animal zoonotic and non-zoonotic disease in a rural farming community in western Kenya.

METHODS

This cross-sectional survey involved 2113 people, their cattle (n = 983) and pigs (n = 91). People and animals were tested for infection or exposure to a wide range of zoonotic and non-zoonotic pathogens. Prevalence estimates, with adjustment for the complex study design, were derived. Evidence for spatial clustering in exposure or infection was identified using the spatial scan statistic.

RESULTS

There was a high prevalence of human parasitism in the community, particularly with hookworm (Ancylostoma duodenale or Necator americanus) (36.3% (95% CI 32.8-39.9)), Entamoeba histolytica/dispar (30.1% (95% CI 27.5-32.8)), and Plasmodium falciparum (29.4% (95% CI 26.8-32.0)). Human infection with Taenia spp. was also prevalent (19.7% (95% CI 16.7-22.7)), while exposure to other zoonotic pathogens was comparatively rarer (Brucella spp., 0.6% (95% CI 0.2-0.9); Coxiella burnetii, 2.2% (95% CI 1.5-2.9); Rift Valley fever, 0.5% (95% CI 0.2-0.8)). A low prevalence of exposure to Brucella spp. was observed in cattle (0.26% (95% CI 0-0.56). This was higher for Rift Valley fever virus (1.4% (95% CI 0.5-2.22)) and C. burnetii (10.0% (95% CI 7.7-12.2)). The prevalence of Taenia spp. cysticercosis was 53.5% (95% CI 48.7-58.3) in cattle and 17.2% (95% CI 9.1-25.3) in pigs. Mycobacterium bovis infection was found in 2.2% of cattle (95% CI 1.3-3.2), while the prevalence of infection with Mycobacterium spp. was 8.2% (95% CI 6.8-9.6) in people.

CONCLUSION

Zoonotic infections in people and animals occur in the context of a wide range of co-endemic pathogens in a rural community in western Kenya. The wide diversity of pathogens under study provides a unique opportunity to explore the distribution and determinants of infection in a multi-pathogen, multi-host system.

Impact of metric and sample size on determining malaria hotspot boundaries

The spatial heterogeneity of malaria suggests that interventions may be targeted for maximum impact. It is unclear to what extent different metrics lead to consistent delineation of hotspot boundaries. Using data from a large community-based malaria survey in the western Kenyan highlands, we assessed the agreement between a model-based geostatistical (MBG) approach to detect hotspots using Plasmodium falciparum parasite prevalence and serological evidence for exposure. Malaria transmission was widespread and highly heterogeneous with one third of the total population living in hotspots regardless of metric tested. Moderate agreement (Kappa = 0.424) was observed between hotspots defined based on parasite prevalence by polymerase chain reaction (PCR)- and the prevalence of antibodies to two P. falciparum antigens (MSP-1, AMA-1). While numerous biologically plausible hotspots were identified, their detection strongly relied on the proportion of the population sampled. When only 3% of the population was sampled, no PCR derived hotspots were reliably detected and at least 21% of the population was needed for reliable results. Similar results were observed for hotspots of seroprevalence. Hotspot boundaries are driven by the malaria diagnostic and sample size used to inform the model. These findings warn against the simplistic use of spatial analysis on available data to target malaria interventions in areas where hotspot boundaries are uncertain.

Species-specific ecological niche modelling predicts different range contractions for Lutzomyia intermedia and a related vector of Leishmania braziliensis following climate change in South America

BACKGROUND

Before 1996 the phlebotomine sand fly Lutzomyia neivai was usually treated as a synonym of the morphologically similar Lutzomyia intermedia, which has long been considered a vector of Leishmania braziliensis, the causative agent of much cutaneous leishmaniasis in South America. This report investigates the likely range changes of both sand fly species in response to a stabilisation climate change scenario (RCP4.5) and a high greenhouse gas emissions one (RCP8.5).

METHODS

Ecological niche modelling was used to identify areas of South America with climates currently suitable for each species, and then the future distributions of these climates were predicted based on climate change scenarios. Compared with the previous ecological niche model of L. intermedia (sensu lato) produced using the GARP algorithm in 2003, the current investigation modelled the two species separately, making use of verified presence records and additional records after 2001. Also, the new ensemble approach employed ecological niche modelling algorithms (including Maximum Entropy, Random Forests and Support Vector Machines) that have been widely adopted since 2003 and perform better than GARP, as well as using a more recent climate change model (HadGEM2) considered to have better performance at higher resolution than the earlier one (HadCM2).

RESULTS

Lutzomyia intermedia was shown to be the more tropical of the two species, with its climatic niche defined by higher annual mean temperatures and lower temperature seasonality, in contrast to the more subtropical L. neivai. These different latitudinal ranges explain the two species' predicted responses to climate change by 2050, with L. intermedia mostly contracting its range (except perhaps in northeast Brazil) and L. neivai mostly shifting its range southwards in Brazil and Argentina. This contradicts the findings of the 2003 report, which predicted more range expansion. The different findings can be explained by the improved data sets and modelling methods.

CONCLUSIONS

Our findings indicate that climate change will not always lead to range expansion of disease vectors such as sand flies. Ecological niche models should be species specific, carefully selected and combined in an ensemble approach.

The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa: A Focus on Human African Trypanosomiasis, Schistosomiasis and Lymphatic Filariasis

Disease control and elimination programmes can benefit greatly from accurate information on the spatial variability of disease risk, particularly when risk is highly spatially heterogeneous. Due to advances in statistical methodology, coupled with the increased availability of geospatial technology, this information is becoming increasingly accessible. In this chapter we describe recent advancements in spatial methods associated with the analysis of disease data measured at the point-level and demonstrate their application to the control and elimination of neglected tropical diseases (NTDs). We further provide information on spatially referenced data sources and software that can be used to create NTD risk maps, concentrating on those that can be freely obtained. Examples relating to three NTDs affecting populations in sub-Saharan Africa are presented throughout the chapter, i.e., human African trypanosomiasis, schistosomiasis and lymphatic filariasis. These three diseases, with differing routes of transmission, control methods and level of spatial heterogeneity, demonstrate the flexibility and applicability of the methods described.

Unveiling a spatial tail breakage outbreak in a lizard population

Many ecological attributes of organisms vary spatially. This strict dependency upon space generally arises by individuals occupying places with the necessary resources and conditions for survival. For lizards, losing the tail is an evolved mechanism that allows them to escape predators or to avoid aggressive intraspecific agonistic interactions. We evaluated the spatial relation of tail loss in a population of the lizard Tropidurus montanus. Our results support the occurrence of a spatial cluster of autotomized lizards. However, we cannot relate the cluster formation to the crowding of neighbouring lizards nor to individuals’ body size. Tail loss in lizards is known to be related to predatory attacks or intraspecific aggression, and we now show that tail autotomy occurs in a non-random way regarding space, and thus is also related to the space occupied by individuals in populations.

The impact of an 8-year mass drug administration programme on prevalence, intensity and co-infections of soil-transmitted helminthiases in Burundi

Background

Soil-transmitted helminth (STH) infections are amongst the most prevalent infections in the world. Mass drug administration (MDA) programmes have become the most commonly used national interventions for endemic countries to achieve elimination. This paper aims to describe the effect of an 8-year MDA programme on the prevalence, intensity of infection and co-infection of STH in Burundi from 2007 to 2014 and critically appraise the trajectory towards STH elimination in the country.

Results

Annual STH parasitological surveys (specifically, a “pilot study” from 2007 to 2011, an “extension study” from 2008 to 2011, and a “national reassessment” in 2014; n = 27,658 children), showed a significant drop in prevalence of infection with any STH (“pooled STH”) between baseline and 2011 in both studies, falling from 32 to 16 % in the pilot study, and from 35 to 16 % in the extension study. Most STH infections were of low intensity according to WHO classification. The national reassessment in 2014 showed that prevalence of pooled STH remained significantly below the prevalence in 2007 in both studies but there was no further decrease in STH prevalence from 2011 levels during this time. Spatial dependence analysis showed that prevalence of Trichuris trichiura and Ascaris lumbricoides had a tendency to cluster over the years, whilst only trends in spatial dependence were evident for hookworm infections. Spatial dependence fluctuated over the course of the programme for Ascaris lumbricoides and Trichuris trichiura. However, spatial trends in spatial dependence were evident in 2010 for Ascaris lumbricoides. Analysis of spatial clustering of intensity of infection and heavy infections revealed that the intensity changed over time for all parasites. Heavy intensity was only evident in Ascaris lumbricoides for 2008 and did not appear in proceeding years and other parasites.

Conclusions

These results demonstrate that sustained annual MDA significantly reduced the prevalence of STH infection in school-age children but was unable to achieve elimination. Additionally, significant decline in prevalence was accompanied by a drop in spatial clustering of infection indicators across all sites from 2008. The lack of consistency in the results of the spatial dependence analysis highlights that MDA programmes can interrupt the normal transmission dynamics of STH parasites.

Electronic supplementary material

The online version of this article (doi:10.1186/s13071-016-1794-9) contains supplementary material, which is available to authorized users.

Mapping Malaria Risk in Low Transmission Settings: Challenges and Opportunities

As malaria transmission declines, it becomes increasingly focal and prone to outbreaks. Understanding and predicting patterns of transmission risk becomes an important component of an effective elimination campaign, allowing limited resources for control and elimination to be targeted cost-effectively. Malaria risk mapping in low transmission settings is associated with some unique challenges. This article reviews the main challenges and opportunities related to risk mapping in low transmission areas including recent advancements in risk mapping low transmission malaria, relevant metrics, and statistical approaches and risk mapping in post-elimination settings.

Elucidating the spatio-temporal dynamics of an emerging wildlife pathogen using approximate Bayesian computation

Emerging pathogens constitute a severe threat for human health and biodiversity. Determining the status (native or non-native) of emerging pathogens, and tracing back their spatio-temporal dynamics, is crucial to understand the eco-evolutionary factors promoting their emergence, to control their spread and mitigate their impacts. However, tracing back the spatio-temporal dynamics of emerging wildlife pathogens is challenging because (i) they are often neglected until they become sufficiently abundant and pose socio-economical concerns and (ii) their geographical range is often little known. Here, we combined classical population genetics tools and approximate Bayesian computation (i.e. ABC) to retrace the dynamics of Tracheliastes polycolpus, a poorly documented pathogenic ectoparasite emerging in Western Europe that threatens several freshwater fish species. Our results strongly suggest that populations of T. polycolpus in France emerged from individuals originating from a unique genetic pool that were most likely introduced in the 1920s in central France. From this initial population, three waves of colonization occurred into peripheral watersheds within the next two decades. We further demonstrated that populations remained at low densities, and hence undetectable, during 10 years before a major demographic expansion occurred, and before its official detection in France. These findings corroborate and expand the few historical records available for this emerging pathogen. More generally, our study demonstrates how ABC can be used to determine the status, reconstruct the colonization history and infer key evolutionary parameters of emerging wildlife pathogens with low data availability, and for which samples from the putative native area are inaccessible.

Plasmodium knowlesi transmission: integrating quantitative approaches from epidemiology and ecology to understand malaria as a zoonosis

The public health threat posed by zoonotic Plasmodium knowlesi appears to be growing: it is increasingly reported across South East Asia, and is the leading cause of malaria in Malaysian Borneo. Plasmodium knowlesi threatens progress towards malaria elimination as aspects of its transmission, such as spillover from wildlife reservoirs and reliance on outdoor-biting vectors, may limit the effectiveness of conventional methods of malaria control. The development of new quantitative approaches that address the ecological complexity of P. knowlesi, particularly through a focus on its primary reservoir hosts, will be required to control it. Here, we review what is known about P. knowlesi transmission, identify key knowledge gaps in the context of current approaches to transmission modelling, and discuss the integration of these approaches with clinical parasitology and geostatistical analysis. We highlight the need to incorporate the influences of fine-scale spatial variation, rapid changes to the landscape, and reservoir population and transmission dynamics. The proposed integrated approach would address the unique challenges posed by malaria as a zoonosis, aid the identification of transmission hotspots, provide insight into the mechanistic links between incidence and land use change and support the design of appropriate interventions.

Spatially variable risk factors for malaria in a geographically heterogeneous landscape, western Kenya: an explorative study

Background

Large reductions in malaria transmission and mortality have been achieved over the last decade, and this has mainly been attributed to the scale-up of long-lasting insecticidal bed nets and indoor residual spraying with insecticides. Despite these gains considerable residual, spatially heterogeneous, transmission remains. To reduce transmission in these foci, researchers need to consider the local demographical, environmental and social context, and design an appropriate set of interventions. Exploring spatially variable risk factors for malaria can give insight into which human and environmental characteristics play important roles in sustaining malaria transmission.

Methods

On Rusinga Island, western Kenya, malaria infection was tested by rapid diagnostic tests during two cross-sectional surveys conducted 3 months apart in 3632 individuals from 790 households. For all households demographic data were collected by means of questionnaires. Environmental variables were derived using Quickbird satellite images. Analyses were performed on 81 project clusters constructed by a traveling salesman algorithm, each containing 50–51 households. A standard linear regression model was fitted containing multiple variables to determine how much of the spatial variation in malaria prevalence could be explained by the demographic and environmental data. Subsequently, a geographically-weighted regression (GWR) was performed assuming non-stationarity of risk factors. Special attention was taken to investigate the effect of residual spatial autocorrelation and local multicollinearity.

Results

Combining the data from both surveys, overall malaria prevalence was 24 %. Scan statistics revealed two clusters which had significantly elevated numbers of malaria cases compared to the background prevalence across the rest of the study area. A multivariable linear model including environmental and household factors revealed that higher socioeconomic status, outdoor occupation and population density were associated with increased malaria risk. The local GWR model improved the model fit considerably and the relationship of malaria with risk factors was found to vary spatially over the island; in different areas of the island socio-economic status, outdoor occupation and population density were found to be positively or negatively associated with malaria prevalence.

Discussion

Identification of risk factors for malaria that vary geographically can provide insight into the local epidemiology of malaria. Examining spatially variable relationships can be a helpful tool in exploring which set of targeted interventions could locally be implemented. Supplementary malaria control may be directed at areas, which are identified as at risk. For instance, areas with many people that work outdoors at night may need more focus in terms of vector control.

Trial registration: Trialregister.nl NTR3496—SolarMal, registered on 20 June 2012

Local spatial clustering of stunting and wasting among children under the age of 5 years: implications for intervention strategies

OBJECTIVE

The present study aimed to evaluate the clustering of undernutrition indicators of children under the age of 5 years in relation to different scales.

DESIGN

A community-based cross-sectional study design was employed. We collected anthropometric data, geographic locations/elevations of households and other data from visited households. We used a retrospective purely spatial Poisson probability model to identify and locate clusters (high rates) of stunting and wasting using the software SaTScan™ version 9·1·1. We ran a logistic regression model to help evaluate the causes of clustering. Settings Six villages in the Meskane Mareko District (38·45763°E, 8·042144°N) of southern Ethiopia.

SUBJECTS

We surveyed 2371 children aged <5 years, who were found in 1744 households.

RESULTS

We found a micro-level variation in the risk of stunting and wasting within the studied district. We found the most likely significant clusters for wasting and severe wasting in two of the six villages. For stunting, a single large cluster size of 390 cases (304·19 expected) in 756 households was identified (relative risk=1·48, P<0·01). For severe stunting, a single cluster size of 106 cases (69·39 expected) in 364 households was identified (relative risk=1·69, P=0·035).

CONCLUSIONS

We conclude that the distribution of wasting and stunting was partly spatially structured. We identified distinct areas within and between villages that have a higher risk than the underlying at-risk population. Our analysis identified the spatial locations of high-risk areas for stunting that could be an input for geographically targeting and optimizing nutritional interventions.

Population Dynamics and Parasite Load of a Foraminifer on Its Antarctic Scallop Host with Their Carbonate Biomass Contributions

We studied the population dynamics and parasite load of the foraminifer Cibicides antarcticus on its host the Antarctic scallop Adamussium colbecki from three localities differing by sea ice cover within western McMurdo Sound, Ross Sea, Antarctica: Explorers Cove, Bay of Sails and Herbertson Glacier. We also estimated CaCO3 biomass and annual production for both species. Cibicides populations varied by locality, valve type, and depth. Explorers Cove with multiannual sea ice had larger populations than the two annual sea ice localities, likely related to differences in nutrients. Populations were higher on Adamussium top valves, a surface that is elevated above the sediment. Depth did not affect Cibicides distributions except at Bay of Sails. Cibicides parasite load (the number of complete boreholes in Adamussium valves) varied by locality between 2% and 50%. For most localities the parasite load was < 20%, contrary to a previous report that ~50% of Cibicides were parasitic. The highest and lowest parasite load occurred at annual sea ice localities, suggesting that sea ice condition is not important. Rather, the number of adults that are parasitic could account for these differences. Cibicides bioerosion traces were categorized into four ontogenetic stages, ranging from newly attached recruits to parasitic adults. These traces provide an excellent proxy for population structure, revealing that Explorers Cove had a younger population than Bay of Sails. Both species are important producers of CaCO3. Cibicides CaCO3 biomass averaged 47-73 kg ha(-1) and Adamussium averaged 4987-6806 kg ha(-1) by locality. Annual production rates were much higher. Moreover, Cibicides represents 1.0-2.3% of the total host-parasite CaCO3 biomass. Despite living in the coldest waters on Earth, these species can contribute a substantial amount of CaCO3 to the Ross Sea and need to be incorporated into food webs, ecosystem models, and carbonate budgets for Antarctica.

Landscape ecology and epidemiology of malaria associated with rubber plantations in Thailand: integrated approaches to malaria ecotoping

The agricultural land use changes that are human-induced changes in agroforestry ecosystems and in physical environmental conditions contribute substantially to the potential risks for malaria transmission in receptive areas. Due to the pattern and extent of land use change, the risks or negatively ecosystemic outcomes are the results of the dynamics of malaria transmission, the susceptibility of human populations, and the geographical distribution of malaria vectors. This review focused basically on what are the potential effects of agricultural land use change as a result of the expansion of rubber plantations in Thailand and how significant the ecotopes of malaria-associated rubber plantations (MRP) are. More profoundly, this review synthesized the novel concepts and perspectives on applied landscape ecology and epidemiology of malaria, as well as approaches to determine the degree to which an MRP ecotope as fundamental landscape scale can establish malaria infection pocket(s). Malaria ecotoping encompasses the integrated approaches and tools applied to or used in modeling malaria transmission. The scalability of MRP ecotope depends upon its unique landscape structure as it is geographically associated with the infestation or reinfestation of Anopheles vectors, along with the attributes that are epidemiologically linked with the infections. The MRP ecotope can be depicted as the hotspot such that malaria transmission is modeled upon the MRP factors underlying human settlements and movement activities, health behaviors, land use/land cover change, malaria vector population dynamics, and agrienvironmental and climatic conditions. The systemic and uniform approaches to malaria ecotoping underpin the stratification of the potential risks for malaria transmission by making use of remotely sensed satellite imagery or landscape aerial photography using unmanned aerial vehicle (UAV), global positioning systems (GPS), and geographical information systems (GIS).

Spatio-temporal factors influencing the occurrence of Syngamus trachea within release pens in the South West of England

Syngamus trachea is a pathogenic tracheal nematode that causes syngamiasis in wild and game birds, especially when birds are managed at high densities. Despite its pathogenic nature, very little is known about its epidemiology and relationship with ambient temperature and humidity. The spatial and temporal modelling of disease was undertaken on two pheasant estates within the South West of England from April 2014 to August 2014. Significant differences between the mean numbers of eggs per gram of soil were identified between pens at both site 1 and site 2 but did not differ significantly between sites. Egg abundance was significantly associated with soil moisture content, with greater egg survival between years in pens with higher average volumetric soil moisture content. Previous years stocking density and pen age were also associated with greater egg survival between years with more eggs being recovered in pens with greater stocking densities, and pens that had been sited longer. The greatest model to explain the variation in the numbers of eggs per gram of soil per pen was a combination of soil moisture content, stocking density and pen age. Larval recovery differed significantly between sites. Larval abundance was significantly and positively associated with temperature and relative humidity at site 1. Similarly, temperature and humidity were also positively and significantly associated with larval abundance at site 2. Rainfall did not influence larval recovery at either site 1 or site 2. The model with the greatest ability to explain larval abundance at both sites, was a combination of temperature, humidity and rainfall. Infection status (positive faecal egg counts) was significantly and positively associated with larval abundance at both sites, but rainfall was only positively associated at site 1. Temperature and humidity were positively associated with infection status at site 2, but not at site 1. The present study highlights the influence of climatic variables on both egg survival and larval abundance, and could therefore be used to develop more targeted treatment strategies around periods of higher disease risk. The frequent use of release pens is a clear factor in the epidemiology of syngamiasis, and it is recommended that pens be rested and/or rotated in order to reduce infection pressure in subsequent flocks.