Leptospirosis Dynamics With Misdiagnosis: A Review

• Published in: Journal of applied mathematics Vol. 2025; no. 1
• Main Authors: Mwongela, Japheth Musingila, Kanyiri, Caroline, Kitetu, Virginia
• Format: Journal Article
• Language: English
• Published: New York John Wiley & Sons, Inc 01.01.2025; Wiley
• Subjects: Analysis; Brazil; Dengue fever; Developing countries; Disease control; Diseases; Epidemics; Epidemiology; Floods; Forecasts and trends; Illnesses; India; Infections; Influenza; Jaundice; LDCs; Leptospirosis; Malaria; Morbidity; Mortality; Philippines; Public health; Socioeconomic factors; Tropical diseases; Typhoid; Viral infections; Zoonoses; Brazil; Philippines; India
• ISSN: 1110-757X; 1687-0042
• DOI: 10.1155/jama/1691122

Leptospirosis is a zoonosis with global distribution, and a wide variety of clinical symptoms often lead to misclassification as other febrile conditions. Clinical misclassification has remained the baseline for the diagnosis of leptospirosis, which poses an uphill challenge to clinical management and epidemiological modeling, which could distort the estimation of our burden of disease, thus further delaying public health interventions. This paper provides an overview of trends in modeling approaches for leptospirosis, with a focus on one of the major challenges of diagnostic inaccuracies in relation to effects on model reliability. Finally, the shortcomings of the classic models are discussed in the context that misdiagnosis has not been well represented, and heeding the strides that have recently been made towards developing ways in which diagnostic uncertainty can be incorporated within these frameworks. Enhanced model accuracy of leptospirosis for robustness will help enhance our understanding of the dynamics of diseases to better inform effective intervention strategies. The importance of interdisciplinary communication between epidemiologists, clinicians, and modelers in addressing the misdiagnosis of infectious disease models is outlined herein.