Infectious Disease
Estimating Diphtheria Reproduction Numbers – Update from the analysis of the 2022 -2023 Diphtheria Outbreak in Kano State (Nigeria) Raoul M KAMADJEU* Raoul M KAMADJEU Oyeladun Okunromade Bola Lawal Muzammil Mohammed
Nigeria has been affected by a large diphtheria outbreak since late 2022, with the epicenter in Kano State from which with 13899 cases (9895 confirmed) were reported. This study focuses on evaluating the basic reproduction number of diphtheria within the ongoing outbreak in Kano State.
We obtained diphtheria outbreak line-list from Aug 2022 to Dec 2023 from Nigeria CDC (NCDC). The effective reproductive number (Rt) a variation of the basic reproduction number reflecting population changing immunity levels and outbreak control measures. Four methods were employed: Exponential Growth (EG), Maximum Likelihood Estimation (ML), Time-Dependent (TD) and Sequential Bayesian (SB). The generation time, needed for estimating Rt, was approximated using the serial interval distribution between onset dates of symptoms for each of the Local Government Area, a State sub-administrative unit. Analyses assumed a chain of transmission in a population initially susceptible, mixing freely, with no imported cases. We used the R0 package in R Studio.
Results revealed two distinct patterns of the outbreak in Kano: a period of low but constant transmission for the first 300 days, with a daily incidence below 25 cases, followed by an explosive burst reaching a peak of 125 cases. The generation time distribution, based on 2,349 values, fits a lognormal distribution with mean = 1.91 and standard deviation = 1.33. Rt estimates were 1.19 (95% CI: 1.17, 1.20) using EG, 1.09 (95% CI: 1.02, 1.73) with ML, and ranged from 0.2 to 3.3 with TD, and 1.0 to 3.19 with SB, reflecting changing transmission dynamics. The observed trend in cases was best modelled by EG, ML, and TD.
This analysis aimed to update the reproduction rate of the diphtheria outbreak in Kano, offering insights into transmission dynamics to inform and adapt control measures. While Rt estimates align with existing findings, caution is necessary in interpretation due to inherent assumptions in their estimation.
