Multisectoral approach in zoonotic disease surveillance

Zoonoses are naturally transmissible between humans and animals. Globally, they account for more than 60% of human infections, 75% of emerging infections, 2.7 million human deaths, and 10% of the total DALYs lost yearly in Africa. In the last three decades, Kenya has had sporadic outbreaks of zoonoses. To increase the speed of reporting and efficiencies in detection and control, a multi-sectoral collaboration in zoonotic disease surveillance (MZDS) between human and animal health workers is essential. In an effort, Zoonotic disease unit (ZDU) in Kenya has been established at national and county levels. A cross sectional study was carried out to determine the level of utilization of multisectoral collaboration and its associated determinants in zoonotic disease surveillance among animal and human healthcare workers in Nakuru County. Quantitative data was gathered from 102 participants and quantitative data from 5 key informants. To test for significant differences, Chi-square and indepen..., Type and Period of Study
Analytical cross-sectional study design was used and the study covered the period between August 20, 2023 and October 15, 2023.
Setting of the Study
The study was conducted in Nakuru County, a third most popular county and located in Rift valley region of Kenya. It is bordered by; Baringo, Laikipia, Nyandarua, Kajiado, Narok, Bomet and Kericho counties. Has an area of 7,496.5km² and a population of 1,603,325. It has physical features like; L. Naivasha a home of millions of flamingos, sanctuary to protect Rothschild giraffe and black rhinos, and Nakuru national park. The site is a hotspot for Anthrax, Brucellosis and Rabies and this formed the basis for purposive selection of the study area.
Inclusion Criteria: Human and Animal Healthcare workers who consented.
Exclusion Criteria: Healthcare workers that were not on duty over the period of the study.
Sampling: A census was conducted.
Data Collection and Tools
A semi-structured pretested interviewer-administered q..., , # Data from: Multisectoral approach in zoonotic disease surveillance

[https://doi.org/10.5061/dryad.g1jwstqzm](https://doi.org/10.5061/dryad.g1jwstqzm)

## Description of the data and file structure

The data herein attached has 3 files. Two excel files (MZDZ2 which contains the raw general data and MZDSCodes file which contain the coding values) and an R file which contains the codes used to produce the results. The excel files is structured in a way that it captures the demographic characteristics of the participants who were involved in disease surveillance, then awareness, attitudes, practices and institutional factors that were associated with multisectoral collaboration. The R file follows the excel file sequence and ends with Chi-square and t-tests were used to assess significant differences.

Describe relationships between data files, missing data codes, other abbreviations used. Be as descriptive as possible.

The Excell files were uploaded and named as MZD AND MZDS1 on to the...

人畜共患病（Zoonoses）是指在人类与动物之间自然传播的疾病。全球范围内，其占人类感染病例的60%以上、新发感染病例的75%，每年造成270万人类死亡，并占非洲年度伤残调整寿命年（Disability-Adjusted Life Years, DALYs）总损失的10%。

过去三十年间，肯尼亚曾出现过人畜共患病的散发病例暴发。为提升报告速度、优化检测与防控效率，人类与动物卫生工作者之间开展人畜共患病监测多部门协作（Multi-sectoral collaboration in zoonotic disease surveillance, MZDS）至关重要。为此，肯尼亚已在国家及郡级层面设立了人畜共患病科（Zoonotic disease unit, ZDU）。

本研究针对奈库鲁郡的人类与动物卫生保健工作者开展横断面研究，旨在评估其人畜共患病监测多部门协作的应用水平及相关影响因素。研究收集了102名参与者的定量数据，以及5名关键知情人的定量数据。为检验组间差异的统计学显著性，本研究采用卡方检验与[原文截断内容]；研究类型与研究周期：本研究采用分析性横断面研究设计，研究周期为2023年8月20日至2023年10月15日。

研究现场：本研究于肯尼亚裂谷地区的奈库鲁郡开展，该郡为肯尼亚第三大郡，周边与巴林戈郡、莱基皮亚郡、恩亚德鲁阿郡、卡贾多郡、纳罗克郡、博梅特郡及基里恰郡接壤。奈库鲁郡占地面积7496.5平方千米，总人口1603325人。境内拥有包括奈瓦沙湖（百万只火烈鸟的栖息地）、罗斯柴尔德长颈鹿与黑犀牛保护保护区及奈库鲁国家公园在内的自然景观。该区域是炭疽、布鲁氏菌病与狂犬病的高发热点区域，因此本研究采用目的性抽样选取该区域作为研究现场。

纳入标准：签署知情同意书的人类与动物卫生保健工作者。
排除标准：研究周期内未在岗的卫生保健工作者。
抽样方式：采用全员普查法。

数据收集与研究工具：本研究采用半结构化、经预试验的访谈员主导式问卷[原文截断]。

# 数据集来源：人畜共患病监测多部门协作方案
[https://doi.org/10.5061/dryad.g1jwstqzm](https://doi.org/10.5061/dryad.g1jwstqzm)

## 数据与文件结构说明
本数据集附带3个文件：2个Excel文件（MZDZ2为原始通用数据表，MZDSCodes为编码值表），以及1个R语言脚本文件（用于生成研究结果的分析代码）。Excel文件的结构可采集参与疾病监测工作的参与者的人口学特征，以及与多部门协作相关的认知、态度、实践与制度因素。R脚本文件遵循Excel文件的分析逻辑，最终采用卡方检验与t检验评估组间差异的统计学显著性。

请详细说明各数据文件间的关联关系、缺失数据编码及其他所用缩写的含义。

已上传的Excel文件被命名为MZD与MZDS1，相关内容[原文截断]