Tick-borne pathogens interactions enhance transmission in cattle and ticks in Ogun, Nigeria

Published: 22 November 2024| Version 1 | DOI: 10.17632/scbsvjgk35.1
Contributors:
, Timothy BAMGBOSE,

Description

The study was conducted in Ogun state, in Southwest Nigeria between March and September 2013. Ticks were collected during the wet season when tick populations are known to be abundant and all species of ticks are likely to be present (Bayer et al., 1984; Walker et al., 2003). The study involved 21 different herds of cattle from eight Local Government Areas covering all agroecological zones of Ogun State, Nigeria (Figure 1). Additionally, ten grazing routes used by cattle in the State were covered by the study. Farms were selected randomly using the snowballing approach as described by Parker et al. (2019), where one farmer provided a link to another for the sampling. Inclusion criteria and ethical consideration The inclusion criteria for animals in this study were limited to those with ticks on their bodies, irrespective of age, or sex. Although these data were not considered for the selection of the animals, they were noted. For a subsequent analysis, it was considered that enrolled animals belonged to eleven cattle breeds: Dageri, Jali, Muturu, N’dama, Red Bororo (RB),** RB cross, RB-WF cross, Segiri, Sokoto Gudali, **White Fulani (WF) and WF-N’dama cross. Consent from the owners was obtained before recruiting the animals for sampling. Approval for the study was obtained from the University of Ibadan Animal Care and Use Research Ethics Committee (UI-ACUREC). Spatial data collection Geographical coordinates of the farm herds and grazing routes were recorded using GPS equipment (Garmin® eTrex 10 Outdoor Handheld GPS Unit Made in USA). The coordinates were instrumental in the construction of the maps depicting the distribution of identified ticks in the sampled areas, utilizing ArcGIS as described by Ekpo et al. (2008). For the analysis of the spatial distribution of tick species in the study region, spatial collected data from previous studies were also included (Adedayo et al., 2018).

Files

Steps to reproduce

Files and variables File: Supplementary_Table_S4.xlsx Description: Tick-borne pathogens prevalence detected in questing ticks (n = 357) by genus-specific end-point PCR assays in Ogun State, Nigeria. Variables * File: Supplementary_Table_S2.xlsx Description: A total of cattle (225) that were sampled Variables Details of cattle sex, age, packed cell volume (PCV), breed, and tick infestation level. File: Supplementary_Table_S3.xlsx Description: Tick-borne pathogens prevalence detected in feeding ticks (n = 1414) by genus-specific end-point PCR assays in Ogun State, Nigeria. Variables Tick Borne Pathogen Identified Code/software Supplementary file S1. Python code for Ordinary Least Squares (OLS) Regression Model. This file contains the complete Python script used for two separate OLS regression models: (i) the first to explore the influence of age, total tick counts, sex, and breed on PCV values*, **and (ii) the second to analyze the impact of tick-borne infections, including both single infections (*Anaplasma spp., Babesia spp., Borrelia spp., Coxiella spp., and Rickettsia spp.) and combinations on PCV values. **Supplementary file S2. **R script detailing the calculation of Yule’s Q and the construction of the co-occurrence network. Supplementary file S3. Python code for simulation of tick-borne pathogen transmission dynamics. This file contains the complete Python script used to simulate the transmission dynamics of tick-borne pathogens among cattle based on different interaction scenarios between pathogens. The script includes definitions for pathogen transmission rates, interaction types (synergistic and competitive), and initial infection conditions, allowing for the modeling of infection trends over six months as presented in Figure 7 of the main text. The code is annotated to guide users through the functions and parameters that govern the simulation. *Supplementary file S4. **List of sequences corresponding to *Coxiella burnetii.

Institutions

Federal University of Agriculture Abeokuta

Categories

Tick-Borne Disease

Licence