Video Experimental Relacionado

Updated: Feb 28, 2026

Microscopy-based Assays for High-throughput Screening of Host Factors Involved in Brucella Infection of Hela Cells

Microscopy-based Assays for High-throughput Screening of Host Factors Involved in Brucella Infection of Hela Cells

Published on: August 5, 2016

Alerta Temprana Espaciotemporal de Brucelosis Humana en la Provincia de Hubei Utilizando Modelos Ecológicos de Series

Qi Chen¹, Buasiyamu Abudunaibi², Xiaoying Zhao²

¹Hubei Provincial Center for Disease Control and Prevention, Wuhan, China.

Zoonoses and public health

|February 25, 2026

Abstracto

Introduction:

This study explored transmission patterns of brucellosis in Hubei Province, a Class II region in China, through analysis of spatiotemporal distribution and environmental factors to provide evidence for precise prevention.

Methods:

We analysed epidemiological data from Hubei Province (2010-2023), including human cases, demographics, livestock numbers and environmental factors. The MaxEnt model was used for spatial risk prediction, while the seasonal autoregressive integrated moving average (SARIMA) model analysed temporal patterns and warning effectiveness.

Results:

Human brucellosis showed a 'rapid rise-effective control-local rebound' pattern, with incidence rates rising from 0.0087/100,000 (2010) to 0.5932/100,000 (2015), declining to 0.1535/100,000 (2019) and rebounding to 0.4508/100,000 (2023). The epidemic displayed seasonal peaks (April-September) and affected primarily males (71.13%) and farmers (76.54%). Spatial distribution showed a 'high-north low-south' pattern, spreading from Suizhou to neighbouring areas. The MaxEnt model identified high-risk areas (probability ≥ 0.713) in livestock-intensive regions, with sheep density (55.1%) and annual mean temperature (9.9%) as key factors. The SARIMA model indicated earliest warnings in high-risk areas (mid-late April), followed by medium-risk (early-mid April) and low-risk areas (late May).

Conclusions:

Brucellosis transmission in Hubei is influenced by the livestock industry, control measures and climate. The integrated MaxEnt-SARIMA model provides risk classification and differentiated warning schemes, offering guidance for targeted prevention across different risk areas.

Palabras clave:

brucelosis modelo de nicho ecológico alerta temprana espaciotemporal

Más Videos Relacionados

Diagnosis and Surgical Treatment of Human Brucellar Spondylodiscitis

Diagnosis and Surgical Treatment of Human Brucellar Spondylodiscitis

Published on: May 23, 2021

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

Videos de Conceptos Relacionados

Steps in Outbreak Investigation

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Biological Clocks and Seasonal Responses

Biological Clocks and Seasonal Responses

The circadian—or biological—clock is an intrinsic, timekeeping, molecular mechanism that allows plants to coordinate physiological activities over 24-hour cycles called circadian rhythms. Photoperiodism is a collective term for the biological responses of plants to variations in the relative lengths of dark and light periods. The period of light-exposure is called the photoperiod.