High endemic levels of typhoid fever in rural areas of Ghana may stem from optimal voluntary vaccination behaviour

Abstract

Typhoid fever has long established itself endemically in rural Ghana despite the availability of cheap and effective vaccines. We used a game-theoretic model to investigate whether the low vaccination coverage in Ghana could be attributed to rational human behaviour. We adopted a version of an epidemiological model of typhoid fever dynamics, which accounted not only for chronic life-long carriers but also for a short-cycle transmission in the immediate environment and a long-cycle transmission via contamination of the water supply. We calibrated the model parameters based on the known incidence data. We found that unless the (perceived) cost of vaccination is negligible, the individually optimal population vaccination rate falls significantly short of the societally optimal population vaccination rate needed to reach herd immunity. We expressed both the herd immunity and the optimal equilibrium vaccination rates in terms of only a few observable parameters such as the incidence rate, demographics, vaccine waning rate and the perceived cost of vaccination relative to the cost of infection. This allowed us not to rely on other uncertain epidemiological model parameters and, in particular, to bypass uncertainties about the role of the carriers in the transmission.

A voluntary use of insecticide treated nets can stop the vector transmission of Chagas disease

“…As usual in vaccination games, see for example [35], individuals weigh the perceived cost of ITN use against the risks of infection. The risk of infection depends on the population-wide ITN use rate.…”

“…This social dilemma is captured by the game theory framework [23]. The framework has now been applied to help model the prevention of many diseases such as African trypanosomiases [24], chikungunya [25], cholera [26], dengue [27], ebola [28], hepatitis B [29], hepatitis C [30], meningitis [31], monkeypox [32], polio [33], toxoplasmosis [34], typhoid [35] and many others, see for example [36] and [22] for recent reviews.…”

Mathematical modelling of the use of insecticide-treated nets for elimination of visceral leishmaniasis in Bihar, India

“…The framework has now been applied to help model the prevention of many diseases such as African trypanosomiases [68], chikungunya [69], cholera [70], dengue [71], Ebola [72], hepatitis B [73], hepatitis C [74], meningitis [75], monkeypox [76], polio [77], toxoplasmosis [78] and many others, see for example [67,79] for recent reviews. It has already been demonstrated theoretically [65,80] as well as empirically [66] that individuals behave rationally and that the high cost of vaccination or ITNs [81] is often the reason why the protection is not adopted.…”

Optimal voluntary and mandatory insect repellent usage and emigration strategies to control the chikungunya outbreak on Reunion Island

“…As the likelihood of contracting the disease is dependent upon the behavior of others within the at-risk population, the resulting strategic interactions between individuals can be modeled using game theory. Game-theoretic frameworks have been adopted to studying optimal individual vaccination strategies for smallpox ( Bauch, Galvani & Earn, 2003 ), influenza ( Galvani, Reluga & Chapman, 2007 ; Shim et al, 2012a ), rubella ( Shim, Kochin & Galvani, 2009 ), measles ( Shim et al, 2012b ), toxoplasmosis ( Sykes & Rychtář, 2015 ), Ebola ( Brettin et al, 2018 ), cholera ( Kobe et al, 2018 ), meningitis (A Martinez, J Machado, E Sanchez, I Erovenko, 2019, unpublished data), hepatitis B ( Chouhan et al, 2020 ), monkeypox ( Bankuru et al, 2020 ), poliomyelitis ( Cheng et al, 2020 ), and typhoid fever ( Acosta-Alonzo et al, 2020 ). It has also been applied to other personal protective measures such as insecticide-treated cattle ( Crawford et al, 2015 ), mosquito repellent ( Dorsett et al, 2016 ), insecticide-treated bed nets ( Broom, Rychtář & Spears-Gill, 2016 ), clean water ( Kobe et al, 2018 ), and clean injecting equipment (K Scheckelhoff, A Ejaz, I Erovenko, 2019, unpublished data).…”