TY - JOUR
T1 - Impact of human mobility on the transmission dynamics of infectious diseases
AU - Khatua, Anupam
AU - Kar, Tapan Kumar
AU - Nandi, Swapan Kumar
AU - Jana, Soovoojeet
AU - Kang, Yun
N1 - Funding Information:
Research of Anupam Khatua is financially supported by the Department of Science and Technology-INSPIRE, Government of India (No. DST/INSPIRE Fellowship/2016/IF160667, dated: September 21, 2016), and the research work of Dr. Soovoojeet Jana is financially supported by WBDSTBT (Memo No. 201(Sanc)/S&T/P/ST/16G-12/2018 dated 19/02/2019). We are also grateful to the anonymous reviewers and editors for their valuable comments and useful suggestions to improve the quality and presentation of the manuscript significantly.
Funding Information:
Research of Anupam Khatua is financially supported by the Department of Science and Technology-INSPIRE, Government of India (No. DST/INSPIRE Fellowship/2016/IF160667, dated: September 21, 2016), and the research work of Dr. Soovoojeet Jana is financially supported by WBDSTBT (Memo No. 201(Sanc)/S&T/P/ST/16G-12/2018 dated 19/02/2019). We are also grateful to the anonymous reviewers and editors for their valuable comments and useful suggestions to improve the quality and presentation of the manuscript significantly.
Publisher Copyright:
© 2020, The Joint Center on Global Change and Earth System Science of the University of Maryland and Beijing Normal University.
PY - 2020/10/1
Y1 - 2020/10/1
N2 - Spatial heterogeneity is an important aspect to be studied in infectious disease models. It takes two forms: one is local, namely diffusion in space, and other is related to travel. With the advancement of transportation system, it is possible for diseases to move from one place to an entirely separate place very quickly. In a developing country like India, the mass movement of large numbers of individuals creates the possibility of spread of common infectious diseases. This has led to the study of infectious disease model to describe the infection during transport. An SIRS-type epidemic model is formulated to illustrate the dynamics of such infectious disease propagation between two cities due to population dispersal. The most important threshold parameter, namely the basic reproduction number, is derived, and the possibility of existence of backward bifurcation is examined, as the existence of backward bifurcation is very unsettling for disease control and it is vital to know from modeling analysis when it can occur. It is shown that dispersal of populations would make the disease control difficult in comparison with nondispersal case. Optimal vaccination and treatment controls are determined. Further to find the best cost-effective strategy, cost-effectiveness analysis is also performed. Though it is not a case study, simulation work suggests that the proposed model can also be used in studying the SARS epidemic in Hong Kong, 2003.
AB - Spatial heterogeneity is an important aspect to be studied in infectious disease models. It takes two forms: one is local, namely diffusion in space, and other is related to travel. With the advancement of transportation system, it is possible for diseases to move from one place to an entirely separate place very quickly. In a developing country like India, the mass movement of large numbers of individuals creates the possibility of spread of common infectious diseases. This has led to the study of infectious disease model to describe the infection during transport. An SIRS-type epidemic model is formulated to illustrate the dynamics of such infectious disease propagation between two cities due to population dispersal. The most important threshold parameter, namely the basic reproduction number, is derived, and the possibility of existence of backward bifurcation is examined, as the existence of backward bifurcation is very unsettling for disease control and it is vital to know from modeling analysis when it can occur. It is shown that dispersal of populations would make the disease control difficult in comparison with nondispersal case. Optimal vaccination and treatment controls are determined. Further to find the best cost-effective strategy, cost-effectiveness analysis is also performed. Though it is not a case study, simulation work suggests that the proposed model can also be used in studying the SARS epidemic in Hong Kong, 2003.
KW - Backward bifurcation
KW - Basic reproduction number
KW - Cost-effectiveness analysis
KW - Nonlinear treatment function
KW - SIRS epidemic model
UR - http://www.scopus.com/inward/record.url?scp=85085202274&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85085202274&partnerID=8YFLogxK
U2 - 10.1007/s40974-020-00164-4
DO - 10.1007/s40974-020-00164-4
M3 - Article
AN - SCOPUS:85085202274
SN - 2363-7692
VL - 5
SP - 389
EP - 406
JO - Energy, Ecology and Environment
JF - Energy, Ecology and Environment
IS - 5
ER -