Vector-borne diseases (VBDs) are a kind of infection caused through the transmission of vectors generated by the bites of infected parasites, bacteria, and viruses, such as ticks, mosquitoes, triatomine bugs, blackflies, and sandflies. If these diseases are not properly treated within a reasonable time frame, the mortality rate may rise. In this work, we propose a set of ontologies that will help in the diagnosis and treatment of vector-borne diseases. For developing VBD's ontology, electronic health records taken from the Indian Health Records website, text data generated from Indian government medical mobile applications, and doctors' prescribed handwritten notes of patients are used as input. This data is then converted into correct text using Optical Character Recognition (OCR) and a spelling checker after pre-processing. Natural Language Processing (NLP) is applied for entity extraction from text data for making Resource Description Framework (RDF) medical data with the help of the Patient Clinical Data (PCD) ontology. Afterwards, Basic Formal Ontology (BFO), National Vector Borne Disease Control Program (NVBDCP) guidelines, and RDF medical data are used to develop ontologies for VBDs, and Semantic Web Rule Language (SWRL) rules are applied for diagnosis and treatment. The developed ontology helps in the construction of decision support systems (DSS) for the NVBDCP to control these diseases.

翻译：虫媒疾病（VBDs）是由受感染寄生虫、细菌和病毒（如蜱虫、蚊子、锥蝽、黑蝇和白蛉）叮咬传播所引起的一类感染性疾病。若未能在合理时间内进行妥善治疗，其死亡率可能上升。本研究提出一组用于辅助虫媒疾病诊断与治疗的本体。在开发虫媒疾病本体时，我们输入了来自印度健康记录网站的电子健康记录、印度政府医疗移动应用程序生成的文本数据以及医生手写的患者处方笔记。这些数据经过预处理后，利用光学字符识别（OCR）和拼写检查器转换为正确文本。采用自然语言处理（NLP）技术从文本数据中提取实体，并借助患者临床数据（PCD）本体构建资源描述框架（RDF）医疗数据。随后，结合基本形式本体（BFO）、国家虫媒疾病控制计划（NVBDCP）指南及RDF医疗数据开发虫媒疾病本体，并应用语义网规则语言（SWRL）规则进行诊断与治疗。所构建的本体有助于为NVBDCP建立决策支持系统（DSS），从而控制这些疾病。