An integrated database on ticks and tick-borne zoonoses in the tropics and subtropics with special reference to developing and emerging countries

Tick-borne zoonoses (TBZ) are emerging diseases worldwide. A large amount of information (e.g. case reports, results of epidemiological surveillance, etc.) is dispersed through various reference sources (ISI and non-ISI journals, conference proceedings, technical reports, etc.). An integrated database-derived from the ICTTD-3 project (http://www.icttd.nl)-was developed in order to gather TBZ records in the (sub-)tropics, collected both by the authors and collaborators worldwide. A dedicated website (http://www.tickbornezoonoses.org) was created to promote collaboration and circulate information. Data collected are made freely available to researchers for analysis by spatial methods, integrating mapped ecological factors for predicting TBZ risk. The authors present the assembly process of the TBZ database: the compilation of an updated list of TBZ relevant for (sub-)tropics, the database design and its structure, the method of bibliographic search, the assessment of spatial precision of geo-referenced records. At the time of writing, 725 records extracted from 337 publications related to 59 countries in the (sub-)tropics, have been entered in the database. TBZ distribution maps were also produced. Imported cases have been also accounted for. The most important datasets with geo-referenced records were those on Spotted Fever Group rickettsiosis in Latin-America and Crimean-Congo Haemorrhagic Fever in Africa. The authors stress the need for international collaboration in data collection to update and improve the database. Supervision of data entered remains always necessary. Means to foster collaboration are discussed. The paper is also intended to describe the challenges encountered to assemble spatial data from various sources and to help develop similar data collections.

Survey for Tick-Borne Zoonoses in the State of Espirito Santo, Southeastern Brazil

Blood samples collected from 201 humans, 92 dogs, and 27 horses in the state of Espirito Santo, Brazil, were tested by polymerase chain reaction, indirect immunofluorescence assays, and indirect enzyme-linked immunosorbent assay for tick-borne diseases (rickettsiosis, ehrlichiosis, anaplasmosis, borreliosis, babesiosis). Our results indicated that the surveyed counties are endemic for spotted fever group rickettsiosis because sera from 70 (34.8%) humans, 7 (7.6%) dogs, and 7 (25.9%) horses were reactive to at least one of the six Rickettsia species tested. Although there was evidence of ehrlichiosis (Ehrlichia canis) and babesiosis (Babesia cams vogeli, Theileria equi) in domestic animals, no human was positive for babesiosis and only four individuals were serologically positive for E. canis. Borrelia burgdorferi-serologic reactive sera were rare among humans and horses, but encompassed 51% of the canine samples, suggesting that dogs and their ticks can be part of the epidemiological cycle of the causative agent of the Brazilian zoonosis, named Baggio-Yoshinari Syndrome.

Estimation of R(0) from the initial phase of an outbreak of a vector-borne infection

The magnitude of the basic reproduction ratio R(0) of an epidemic can be estimated in several ways, namely, from the final size of the epidemic, from the average age at first infection, or from the initial growth phase of the outbreak. In this paper, we discuss this last method for estimating R(0) for vector-borne infections. Implicit in these models is the assumption that there is an exponential phase of the outbreaks, which implies that in all cases R(0) > 1. We demonstrate that an outbreak is possible, even in cases where R(0) is less than one, provided that the vector-to-human component of R(0) is greater than one and that a certain number of infected vectors are introduced into the affected population. This theory is applied to two real epidemiological dengue situations in the southeastern part of Brazil, one where R(0) is less than one, and other one where R(0) is greater than one. In both cases, the model mirrors the real situations with reasonable accuracy.