登革热负担和影响洪都拉斯严重性的因素:描述性和分析性研究
Melba Zúniga-Gutiérrez1, Marlon Meléndez2, Saroni Shadai Rodríguez Montoya2
1Universidad Nacional Autónoma de Honduras, Research Institute in Medical Sciences and Right to Health, Epidemiology Postgraduate Program Tegucigalpa, Honduras.
Revista da Sociedade Brasileira de Medicina Tropical
|June 19, 2024
概括
洪都拉斯的登革热严重程度与年轻年龄组 (19岁以下) 以及拉巴斯和科班等特定地区有关. 这项研究分析了14000多例病例,以确定严重登革热结果的关键风险因素.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 传染性疾病 传染性疾病
背景情况:
- 登革热在洪都拉斯构成了重大公共卫生挑战,导致大量的发病率和死亡率.
- 了解登革热的流行病学模式和风险因素对于有效的疾病控制至关重要.
研究的目的:
- 分析洪都拉斯2016-2022年登革热病例数据.
- 确定与登革热严重程度相关的人口和地理因素.
主要方法:
- 一项具有分析组成部分的描述性研究,利用来自国家病毒学实验室 (2016-2022) 的数据.
- 使用顺序后勤回归来分类登革热病例:没有警告信号的登革热 (DWOS),有警告信号的登革热 (DWS) 和严重的登革热 (SD).
主要成果:
- 在14687例登革热病例中,50.1%为DWOS,36.5%为DWS,13.4%为SD.
- 年龄组1-19岁,男性性别和居住在拉巴斯,科班或瓦莱省的住所与增加DWS和SD风险显著相关.
- 为这些关联计算了特定的几率比率 (OR) 和95%置信区间 (CI).
结论:
- 登革热在洪都拉斯表现出流行性行为,在2015年和2019年观察到流行病峰值.
- 预测严重登革热的关键因素包括19岁以下的年龄,男性性别和位于拉巴斯,科班或瓦莱的地理位置.
- 调查结果强调,需要针对高风险人群和地区进行有针对性的干预.
相关概念视频
Factors Affecting Illness
5.4K
When a person's physical, emotional, intellectual, social development or spiritual functioning is compromised, this deviation from a healthy normal state is called illness. Illness creates stress that in turn harms individuals. Irritation, anger, denial, hopelessness, and fear are behavioral and emotional changes an individual experiences in the phases of illness. A variety of factors influence a person's health and well-being.
For instance, risk factors are connected to illness,...
For instance, risk factors are connected to illness,...
5.4K
Causality in Epidemiology
2.2K
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
2.2K
Bias in Epidemiological Studies
1.7K
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:
1.7K
Statistical Methods for Analyzing Epidemiological Data
1.3K
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:
1.3K
Principles of Disease Surveillance
856
Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
856
Infectious Diseases and Their Occurrence
97
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable...
97


