  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.
