MODELING DIPHTHERIA TRANSMISSION AND CONTROL STRATEGIES IN NIGERIA USING A COMPARTMENTAL MODEL APPROACH

Abstract

Diphtheria remains a significant public health concern in many developing countries, 
particularly in regions characterized by low immunization coverage and undiagnosed 
infections. One of the major challenges in controlling the disease is the often
overlooked contribution of asymptomatic individuals, who may silently sustain and 
propagate transmission within the population. This study develops a deterministic 
diphtheria vaccine–treatment model to describe the transmission dynamics of 
diphtheria within the Nigerian population and to evaluate the impact of different 
vaccination and treatment strategies on disease prevention and control. Model 
parameters were estimated using reported diphtheria incidence data obtained from 
the Nigeria Centre for Disease Control covering the period from 1 December 2022 to 
31 July 2023. The basic reproduction number, (R0), was derived analytically, and the 
estimated mean value of (R0 = 6.010) indicates sustained endemic transmission and 
suggests that existing intervention strategies are insufficient to effectively curtail 
disease spread. Sensitivity analysis identified key epidemiological parameters driving 
diphtheria transmission dynamics, including the recruitment rate, waning immunity rate 
from fully vaccinated individuals to the susceptible class, asymptomatic transmission 
rate, and waning immunity rate from partially vaccinated individuals to susceptibles. 
The findings underscore the critical need for comprehensive control strategies that 
extend beyond symptomatic case management. Such strategies should include 
sustained immunization campaigns, booster vaccination programmes, enhanced 
surveillance, and targeted interventions aimed at reducing asymptomatic transmission. 
The proposed model provides valuable quantitative insights for evidence-based 
diphtheria prevention and control policies, particularly in resource-constrained 
settings.