Analysis of Recurrent Times-to-Clinical Malaria Episodes and Plasmodium falciparum Parasitemia: A Joint Modeling Approach Applied to a Cohort Data - Stanley, Christopher C.; Mukaka, Mavuto; Kazembe, Lawrence N.; Buchwald, Andrea G.; Mathanga, Don P.; Laufer, Miriam K.; Chirwa, Tobias F. (Frontiers in Epidemiology, 2022)
Background: Recurrent clinical malaria episodes due to Plasmodium falciparum (Pf) parasite infection are common in endemic regions. With each infection, acquired immunity develops, making subsequent disease episodes less likely. To capture the effect of acquired immunity to malaria, it may be necessary to model recurrent clinical disease episodes jointly with Pf parasitemia data. A joint model of longitudinal parasitemia and time-to-first clinical malaria episode (single-event joint model) may be inaccurate since due to acquired immunity is lost when subsequent episodes are excluded. This study informativeness assessed whether joint modelling of recurrent clinical malaria episodes and parasitemia is more accurate than a single-event joint model where the subsequent episodes are ignored. Methods: The single event joint model is comprised of Cox Proportional Hazards (PH) sub-model for time-to-first clinical malaria episode and Negative Binomial (NB) mixed-effects sub-model for the longitudinal parasitemia. The recurrent events joint model extends the survival sub-model to a Gamma shared frailty model in order to include all recurrent clinical episodes. The models were applied to cohort data from Malawi. Simulations were also conducted to assess the performance of the model under different conditions. Results: The recurrent events joint model yielded higher hazard ratios of clinical malaria, was more precise and in most cases produced smaller standard errors than the single-event joint model; hazard ratio (HR)=1.42, [95% confidence interval [CI]: 1.22, 2.03] vs. HR=1.29, [95% CI:1.60, 2.45] among participants who reported not to use LLINs every night compared to those who used the nets nightly; HR=0.96, [ 95% CI: 0.94, 0.98] vs. HR=0.81, [95% CI: 0.75, 0.88] for each 1-year increase in participants’ age; and HR=1.36, [95% CI: 1.05, 1.75] vs. HR=1.10, [95% CI: 0.83, 4.11] for observations during the rainy season compared to dry season. Conclusion: The recurrent events joint model in this paper provides a way of estimating risk of malaria clinical malaria in a cohort where the effect of immunity on malaria disease acquired due to P falciparum parasitemia with aging is captured. The simulation study has shown that if correctly specified, the recurrent events joint model can give risk estimates with low bias.