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Background: Sensory processing refers to receiving, organizing, and interpreting sensory stimuli from the sensory system. Unlike other neurodevelopmental disorders, knowledge about the sensory processing abilities of children with cerebral palsy (CP) is lacking. Objective: To study the difference in sensory processing abilities of children with cerebral palsy in comparison to age matched typically developing children (TDC). Methods and Material: A cross-sectional analysis of sensory processing abilities of children with CP and TDC was performed from July 2018 through February 2020. The child sensory profile2 (CSP2) caregiver questionnaire was used to detect sensory processing differences (SPD) across nine sensory domains and four sensory processing patterns. A comparison was made between the two study groups as well as between the CP subtypes. Result: Around 226 children with CP and 58 TDC were screened. Finally, 150 children with CP and 50 TDC were enrolled. Probable SPD (>1SD) was observed in (121/150) 80.7% of children with CP compared to (13/50) 26% in TDC (p < 0.001). Definite SPD (>2SD) was seen in 40.7% (61/150) of children with CP vs. none in TDC (p < 0.001). The body position domain which tests the vestibular and proprioceptive processing was primarily affected in CP. Most children with CP fell under the "bystander" pattern suggesting poor registration of sensory stimuli. No significant difference in the pattern of sensory processing was observed between the CP subtypes. Prevalence of definite SPD positively correlated with the gross motor functional classification system level. Conclusion: Sensory processing abilities of children with CP differ significantly from TDC. Proprioceptive and vestibular sensory processing is primarily affected in CP. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected the world, leading to significant morbidity and mortality. Various meteorological parameters are considered essential for the viability and transmission of the virus. Multiple reports from various parts of the world suggest a correlation between the disease spread and air pollution severity. This study was carried out to identify the relationship between meteorological parameters, air pollution, and COVID-19 in New Delhi, one of the worst-affected states in India. We studied air pollution and meteorological parameters in New Delhi, India. We obtained data about COVID-19 occurrence, meteorological parameters, and air pollution indicators from various sources from April 1, 2020, until November 12, 2020. We performed correlational analysis and employed autoregressive distributed lag models to identify the relationship between COVID-19 cases, air pollution and meteorological parameters. We found a significant impact of particulate matter (PM) 2.5, PM10, and meteorological parameters on COVID-19. There was a significant positive correlation between daily COVID19 cases and COVID-19-related deaths with PM2.5 and PM10 levels. Increasing temperature and wind speed were associated with a reduction in the number of cases, while increasing humidity was associated with increased cases. This study demonstrated a significant association between PM2.5 and PM10 and daily COVID-19 cases and COVID-19-related mortality. This knowledge will likely help us prepare well for the future and implement air pollution control measures for other airborne disease epidemics. [ABSTRACT FROM AUTHOR]