Laager, Mirjam. Mathematical modelling of dog rabies transmission in N’Djamena, Chad. 2018, Doctoral Thesis, University of Basel, Faculty of Science.
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Official URL: http://edoc.unibas.ch/diss/DissB_12720
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Abstract
Rabies is a viral disease that is transmitted by bite and is fatal after the onset of symptoms. All warm blooded animals are susceptible to rabies and a wide range of species including foxes, wolves, jackals, raccoons, mongooses and bats act as reservoir hosts. Approximately 60,000 people die of rabies every year, mainly in Africa and Asia. The main source of human rabies is the domestic dog. Rabies in humans is preventable by timely administration of post-exposure prophylaxis, with a reduced schedule of administration if the person was protected by pre-exposure prophylaxis. Mass vaccination of dogs is considered effective in preventing human exposure and oral vaccine baits were used to eliminate rabies from foxes in central and western Europe.
In N’Djamena, the capital of Chad, rabies is endemic with approximately one confirmed case of dog rabies per week. Each dog exposes on average two humans. In 2012 and 2013 two mass vaccination campaigns of dogs were conducted, reaching a coverage of more than 70% in both years. The campaigns interrupted transmission for nine months, but a resurgence of cases led to re-establishment of rabies at the pre-intervention endemic state. To better understand the
movement and contact behaviour of dogs, 300 geo-located contact sensors were deployed on dogs in three different quarters of N’Djamena in 2016.
We developed three mathematical models of rabies transmission, calibrated to the incidence data and coverage levels from the campaigns and data on dog movement and contacts from the geo-located contact sensors. We used an ordinary differential equation model to assess the effect of the vaccination campaigns and found that after the campaigns, the effective reproductive ratio dropped below one. Implementing a stochastic version of the model with the Gillespie algorithm confirmed the interruption of transmission. We found that population turnover contributed more to the decrease of vaccination coverage after the campaigns than individual immunity loss. Possible reasons for the resurgence of cases after the campaigns include spatial heterogeneity of vaccination coverage and dog density, underreporting and importation of latent dogs from the surroundings of N’Djamena. We developed a deterministic metapopulation model with importation of latent dogs to investigate the potential reasons for the resurgence seen in 2014. Our results indicate that importation of latently infected dogs better explains the incidence data than heterogeneity or underreporting. Because importation seems to be the most likely reason for the resurgence in cases, we investigated the chains of transmission triggered by imported cases. In order to realistically reproduce the contact heterogeneity at individual level, we used data from 300 geo-located contact sensors to build a network of 5000 dogs. Since there is no established method for expanding a network to a network with more nodes, we have developed and validated a network construction algorithm. We developed an individual based model and calibrated the transmission rate such that the simulation results correspond to outbreak data from two quarters in N’Djamena. We have shown that 70% coverage prevents major but not minor outbreaks. Since highly connected dogs hold a critical role in rabies transmission, vaccinating such dogs could increase the effect of vaccination strategies. Vaccinating dogs is an effective and equitable way of reducing human exposure and should therefore be an inherent of part rabies control programmes in endemic settings. However, in the absence of dog population management, population turnover quickly reduces vaccination coverage and reintroduction from surrounding areas or spillovers from wildlife reservoirs threaten the gains of mass dog vaccination campaigns. This suggests that maintaining high vaccination coverage by either repeated mass vaccination campaigns or continuous vaccination of dogs as well as oral vaccination of reservoirs (which was not investigated here) might be part of the best intervention package for settings like N’Djamena.
In N’Djamena, the capital of Chad, rabies is endemic with approximately one confirmed case of dog rabies per week. Each dog exposes on average two humans. In 2012 and 2013 two mass vaccination campaigns of dogs were conducted, reaching a coverage of more than 70% in both years. The campaigns interrupted transmission for nine months, but a resurgence of cases led to re-establishment of rabies at the pre-intervention endemic state. To better understand the
movement and contact behaviour of dogs, 300 geo-located contact sensors were deployed on dogs in three different quarters of N’Djamena in 2016.
We developed three mathematical models of rabies transmission, calibrated to the incidence data and coverage levels from the campaigns and data on dog movement and contacts from the geo-located contact sensors. We used an ordinary differential equation model to assess the effect of the vaccination campaigns and found that after the campaigns, the effective reproductive ratio dropped below one. Implementing a stochastic version of the model with the Gillespie algorithm confirmed the interruption of transmission. We found that population turnover contributed more to the decrease of vaccination coverage after the campaigns than individual immunity loss. Possible reasons for the resurgence of cases after the campaigns include spatial heterogeneity of vaccination coverage and dog density, underreporting and importation of latent dogs from the surroundings of N’Djamena. We developed a deterministic metapopulation model with importation of latent dogs to investigate the potential reasons for the resurgence seen in 2014. Our results indicate that importation of latently infected dogs better explains the incidence data than heterogeneity or underreporting. Because importation seems to be the most likely reason for the resurgence in cases, we investigated the chains of transmission triggered by imported cases. In order to realistically reproduce the contact heterogeneity at individual level, we used data from 300 geo-located contact sensors to build a network of 5000 dogs. Since there is no established method for expanding a network to a network with more nodes, we have developed and validated a network construction algorithm. We developed an individual based model and calibrated the transmission rate such that the simulation results correspond to outbreak data from two quarters in N’Djamena. We have shown that 70% coverage prevents major but not minor outbreaks. Since highly connected dogs hold a critical role in rabies transmission, vaccinating such dogs could increase the effect of vaccination strategies. Vaccinating dogs is an effective and equitable way of reducing human exposure and should therefore be an inherent of part rabies control programmes in endemic settings. However, in the absence of dog population management, population turnover quickly reduces vaccination coverage and reintroduction from surrounding areas or spillovers from wildlife reservoirs threaten the gains of mass dog vaccination campaigns. This suggests that maintaining high vaccination coverage by either repeated mass vaccination campaigns or continuous vaccination of dogs as well as oral vaccination of reservoirs (which was not investigated here) might be part of the best intervention package for settings like N’Djamena.
Advisors: | Utzinger, Jürg and Chitnis, Nakul and Keeling, Matt |
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Faculties and Departments: | 05 Faculty of Science 09 Associated Institutions > Swiss Tropical and Public Health Institute (Swiss TPH) > Former Units within Swiss TPH > Health Impact Assessment (Utzinger) |
UniBasel Contributors: | Chitnis, Nakul |
Item Type: | Thesis |
Thesis Subtype: | Doctoral Thesis |
Thesis no: | 12720 |
Thesis status: | Complete |
Number of Pages: | 1 Online-Ressource (vii, 96 Seiten) |
Language: | English |
Identification Number: |
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edoc DOI: | |
Last Modified: | 30 Nov 2018 05:30 |
Deposited On: | 07 Sep 2018 08:38 |
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