Dataset Information

Modeling disease vector occurrence when detection is imperfect: infestation of Amazonian palm trees by triatomine bugs at three spatial scales.

ABSTRACT:

Background

Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae), the most important vectors of Chagas disease (CD) in northern South America.

Methodology/principal findings

The probability of detecting triatomines in infested palms is estimated by repeatedly sampling each palm. This knowledge is used to derive an unbiased estimate of the biologically relevant probability of palm infestation. We combine maximum-likelihood analysis and information-theoretic model selection to test the relationships between environmental covariates and infestation of 298 Amazonian palm trees over three spatial scales: region within Amazonia, landscape, and individual palm. Palm infestation estimates are high (40-60%) across regions, and well above the observed infestation rate (24%). Detection probability is higher ( approximately 0.55 on average) in the richest-soil region than elsewhere ( approximately 0.08). Infestation estimates are similar in forest and rural areas, but lower in urban landscapes. Finally, individual palm covariates (accumulated organic matter and stem height) explain most of infestation rate variation.

Conclusions/significance

Individual palm attributes appear as key drivers of infestation, suggesting that CD surveillance must incorporate local-scale knowledge and that peridomestic palm tree management might help lower transmission risk. Vector populations are probably denser in rich-soil sub-regions, where CD prevalence tends to be higher; this suggests a target for research on broad-scale risk mapping. Landscape-scale effects indicate that palm triatomine populations can endure deforestation in rural areas, but become rarer in heavily disturbed urban settings. Our methodological approach has wide application in infectious disease research; by improving eco-epidemiological parameter estimation, it can also significantly strengthen vector surveillance-control strategies.

SUBMITTER: Abad-Franch F

PROVIDER: S-EPMC2830460 | biostudies-literature | 2010 Mar

REPOSITORIES: biostudies-literature

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Publications

Modeling disease vector occurrence when detection is imperfect: infestation of Amazonian palm trees by triatomine bugs at three spatial scales.

Abad-Franch Fernando F Ferraz Gonçalo G Campos Ciro C Palomeque Francisco S FS Grijalva Mario J MJ Aguilar H Marcelo HM Miles Michael A MA

PLoS neglected tropical diseases 20100302 3

<h4>Background</h4>Failure to detect a disease agent or vector where it actually occurs constitutes a serious drawback in epidemiology. In the pervasive situation where no sampling technique is perfect, the explicit analytical treatment of detection failure becomes a key step in the estimation of epidemiological parameters. We illustrate this approach with a study of Attalea palm tree infestation by Rhodnius spp. (Triatominae), the most important vectors of Chagas disease (CD) in northern South ...[more]

PMID: 20209149

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Project description:Contemporary patterns of land use and global climate change are modifying regional pools of parasite host species. The impact of host community changes on human disease risk, however, is difficult to assess due to a lack of information about zoonotic parasite host assemblages. We have used a recently developed method to infer parasite-host interactions for Chagas Disease (CD) from vector-host co-occurrence networks. Vector-host networks were constructed to analyze topological characteristics of the network and ecological traits of species' nodes, which could provide information regarding parasite regional dispersal in Mexico. Twenty-eight triatomine species (vectors) and 396 mammal species (potential hosts) were included using a data-mining approach to develop models to infer most-likely interactions. The final network contained 1,576 links which were analyzed to calculate centrality, connectivity, and modularity. The model predicted links of independently registered Trypanosoma cruzi hosts, which correlated with the degree of parasite-vector co-occurrence. Wiring patterns differed according to node location, while edge density was greater in Neotropical as compared to Nearctic regions. Vectors with greatest public health importance (i.e., Triatoma dimidiata, T. barberi, T. pallidipennis, T. longipennis, etc), did not have stronger links with particular host species, although they had a greater frequency of significant links. In contrast, hosts classified as important based on network properties were synanthropic mammals. The latter were the most common parasite hosts and are likely bridge species between these communities, thereby integrating meta-community scenarios beneficial for long-range parasite dispersal. This was particularly true for rodents, >50% of species are synanthropic and more than 20% have been identified as T. cruzi hosts. In addition to predicting potential host species using the co-occurrence networks, they reveal regions with greater expected parasite mobility. The Neotropical region, which includes the Mexican south and southeast, and the Transvolcanic belt, had greatest potential active T. cruzi dispersal, as well as greatest edge density. This information could be directly applied for stratification of transmission risk and to design and analyze human-infected vector contact intervention efficacy.

Project description:BackgroundTwo health concerns primarily related to triatomine bugs are transmission of Trypanosoma cruzi through infective feces, and allergic reactions induced by triatomine bites. In the Southwestern United States, reduviid bugs bites commonly cause insect allergy. In South China, four cases of anaphylactic shock have been reported after this bite exposure. To further classify the species of these bugs and confirm the sensitization of the triatomine saliva, we caught triatomine bugs from the region where the bites occurred and performed phylogenetic and immunohistochemical (IHC) analysis.MethodsTriatomine bugs were collected in Donghai Island of Zhanjiang City in South China. The genomic DNA was extracted from three legs of the bugs. The fragments of mitochondrial 16S rRNA, cytochrome c oxidase subunit I (COI) gene and nuclear ribosomal 18S and 28S rRNA genes were obtained by PCR and sequenced. A phylogenetic tree was constructed based on the sequence of 16S rRNA gene using a maximum likelihood method with MEGA 7.0 software. Trypanosomal specific fragments and vertebrate COI genes were amplified from the fecal DNA to detect the infection of trypanosomes and analyze the blood feeding patterns, respectively. Paraffin-embedded sections were then prepared from adult triatomines and sent for IHC staining.ResultsWe collected two adult triatomine bugs in Donghai Island. Morphological and molecular analyses indicated that the triatomines were Triatoma rubrofasciata. No fragments of T. cruzi or other trypanosomes were detected from the fecal DNA. Mitochondrial gene segments of Homo sapiens and Mus musculus were successfully amplified. The allergens which induced specific IgE antibodies in human serum were localized in the triatomine saliva by IHC assay.ConclusionsThe two triatomine bugs from Donghai Island were T. rubrofasciata. They had bitten humans and mice. Their saliva should contain the allergens related to the allergic symptoms and even anaphylactic shock of exposed residents. Great consideration should be given to this triatomine bugs due to their considerable distribution and potential threat to public health in South China.

Dataset Information

Modeling disease vector occurrence when detection is imperfect: infestation of Amazonian palm trees by triatomine bugs at three spatial scales.

Background

Methodology/principal findings

Conclusions/significance

Publications

Modeling disease vector occurrence when detection is imperfect: infestation of Amazonian palm trees by triatomine bugs at three spatial scales.

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