Mathematical modelling of the transmission dynamics of contagious bovine pleuropneumonia reveals minimal target profiles for improved vaccines and diagnostic assays

Abstract

Contagious bovine pleuropneumonia (CBPP) is a cattle disease that has hampered the development of the livestock sector in sub-Saharan Africa. Currently, vaccination with a live vaccine strain is its recommended control measure although unofficial antimicrobial use is widely practiced. Here, modelling techniques are used to assess the potential impact of early elimination of infected cattle via accurate diagnosis on CBPP dynamics. A herd-level stochastic epidemiological model explicitly incorporating test sensitivity and specificity is developed. Interventions by annual vaccination, annual testing and elimination and a combination of both are implemented in a stepwise manner and their effectiveness compared by running 1000 simulations per intervention over ten years. The model predicts that among the simulated interventions, the ones likely to eliminate the disease from an isolated herd all involved annual vaccination of more than 75% of the animals with a vaccine that protects for at least 18 months combined with annual testing (and elimination of positive reactors) of 75% of the animals every six months after vaccination. The highest probability of disease elimination was 97.5% and this could occur within a median of 2.3 years. Generally, our model predicts that regular testing and elimination of positive reactors using improved tests will play a significant role in minimizing CBPP burden especially in the current situation where improved vaccines are yet to be developed.

Fig 1. A compartmental model for the dynamics of CBPP that incorporates testing and elimination of positive reactors.

The model is of the type “SVEIMQR” where S represents the susceptible, V the vaccinated, E the exposed, I the infectious, M the eliminated, Q the chronically infected and R the recovered state. Testing and vaccination are discrete time events and are thus represented by the dashed arrows and all the other events are continuous and are represented by the non-dashed arrows.

Fig 2. Disease elimination chances for the different intervention scenarios.

Elimination chance represents the fraction of simulations in which the disease dies out before the end of simulation time. As an example, scenario “AVT:vac37.5%_8months_test75%_se64%” represents an annual vaccination and testing strategy in which the effective vaccination coverage is 37.5% with a vaccine that protects for eight months together with testing of 75% of the animals with a 64% sensitive test.

Fig 3. Boxplots for the predicted effects of the various intervention scenarios on the epidemic duration.

Panel (a) presents epidemic durations under the baseline and annual vaccination (AV) strategies. Panel (b) depicts epidemic durations under the annual vaccination and testing (AVT) strategy for different test sensitivity and vaccination coverage. Panel (c) presents epidemic durations under the annual testing (AT) strategy for varying test sensitivity and tested fraction. Panel (d) shows epidemic durations under the annual vaccination and testing (AVT) strategy for varying vaccine protection duration and vaccination coverage. As an example, scenario “AVT:vac37.5%_8months_test75%_se64%” represents an annual vaccination and testing strategy in which the effective vaccination coverage is 37.5% with a vaccine that protects for eight months together with testing of 75% of the animals with a 64% sensitive test.

Fig 4. Boxplots for the predicted effects of the various intervention scenarios on the cumulative number of fatalities.

Panel (a) presents the cumulative number of fatalities under the baseline and annual vaccination (AV) strategies. Panel (b) depicts the cumulative number of fatalities under the annual vaccination and testing (AVT) strategy for different test sensitivity and vaccination coverage. Panel (c) presents the cumulative number of fatalities under the annual testing (AT) strategy for varying test sensitivity and tested fraction. Panel (d) shows the cumulative number of fatalities under the annual vaccination and testing (AVT) strategy for varying vaccine protection duration and vaccination coverage. As an example, scenario “AVT:vac37.5%_8months_test75%_se64%” represents an annual vaccination and testing strategy in which the effective vaccination coverage is 37.5% with a vaccine that protects for eight months together with testing of 75% of the animals with a 64% sensitive test.

Fig 5. Boxplots for the predicted effects of the various intervention scenarios on the cumulative number eliminated (panel a-c) and false negative animals (panel d-f).

Panel (a) presents the cumulative number eliminated under the annual testing (AT) strategy for varying test sensitivity and tested fraction. Panel (b) depicts the cumulative number eliminated under the annual vaccination and testing (AVT) strategy for varying vaccine protection duration and vaccination coverage. Panel (c) presents the cumulative number eliminated under annual vaccination and testing (AVT) strategy for varying test sensitivity and vaccination coverage. Panel (d) presents the cumulative number of false negative animals under the annual testing (AT) strategy for varying test sensitivity and tested fraction. Panel (e) depicts the cumulative number of false negative animals under the annual vaccination and testing (AVT) strategy for varying vaccine protection duration and vaccination coverage. Panel (f) presents the cumulative number of false negative animals under annual vaccination and testing (AVT) strategy for varying test sensitivity and vaccination coverage. As an example, scenario “AVT:vac37.5%_8months_test75%_se64%” represents an annual vaccination and testing strategy in which the effective vaccination coverage is 37.5% with a vaccine that protects for eight months together with testing of 75% of the animals with a 64% sensitive test.

Fig 6. Boxplots for the predicted effects of the various intervention scenarios on the cumulative number of false positive animals.

Panel (a) presents the cumulative number of false positive animals under the annual testing (AT) strategy for varying test sensitivity and tested fraction. Panel (b) depicts the cumulative number of false positive animals under the annual vaccination and testing (AVT) strategy for varying vaccine protection duration and vaccination coverage. Panel (c) presents the cumulative number of false positive animals under annual vaccination and testing (AVT) strategy for varying test sensitivity and vaccination coverage.