Reduction in severity of all-cause gastroenteritis requiring hospitalisation in children vaccinated against rotavirus in Malawi

Abstract

Background: Rotavirus is the major cause of severe gastroenteritis in children aged <5 years. Introduction of Rotarix rotavirus vaccine (RV1) in Malawi in 2012 has reduced rotavirus-associated hospitalisations and diarrhoeal mortality. However, RV1 impact on gastroenteritis severity remains unknown. We conducted a hospital-based surveillance study to assess RV1 impact on gastroenteritis severity in children aged <5 years, in Malawi. Methods: Stool samples were collected from children hospitalised with acute gastroenteritis from December 2011 to October 2019. Gastroenteritis severity was determined using Ruuska and Vesikari scores. Rotavirus was detected in stool using Enzyme Immunoassay. Rotavirus genotypes were determined using nested RT-PCR. Associations between RV1 vaccination and gastroenteritis severity were investigated using adjusted linear regression. Results: In total, 3,159 children were recruited. After adjusting for Mid-Upper Arm Circumference, age, weight, gender and receipt of other vaccines, all-cause gastroenteritis severity scores were 2.21 units lower (95% CI 1.85, 2.56; p<0.001) among RV1-vaccinated (n=2,224) compared to RV1-unvaccinated children (n=935); the decrease was comparable between rotavirus-positive and rotavirus-negative cases in all age groups. The reduction in severity score was observed against every rotavirus genotype, although the magnitude was smaller among those infected with G12P[6] compared to the remaining genotypes (p=0.011). Other than RV1 vaccination, age was the only variable associated with gastroenteritis severity. Each one-year increment in age was associated with a decrease of 0.43 severity score (95% CI 0.26, 0.60; p<0.001). Conclusion: Our findings provide additional evidence of RV1 impact in a high disease burden, low-income country, lending further support to rotavirus vaccine programme in Malawi.

Relaxation of the parameter independence assumption in the bootComb R package

“…This package for the statistical computing environment R (R Core Team, 2021) allows researchers to derive confidence intervals (CIs) with correct coverage for combinations of independently estimated parameters. Important applications include adjusting a prevalence for estimated test sensitivity and specificity (e.g., Mandolo et al, 2021) or combining conditional prevalence estimates (e.g., Stockdale et al, 2020).…”