Hair Loss (Alopecia) in Children: Etiology, Epidemiology, Clinical Characteristics, Differential Diagnosis

Antonova, S. B.; Уфимцева, М. А.; Bochkarev, Yu.M.; Nikolaeva, K. I.; Savchenko, N.V.

doi:10.24110/0031-403x-2020-99-6-148-154

Pediatria

2020

DOI: 10.24110/0031-403x-2020-99-6-148-154

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Hair Loss (Alopecia) in Children: Etiology, Epidemiology, Clinical Characteristics, Differential Diagnosis

S. B. Antonova¹,

М. А. Уфимцева²,

Yu.M. Bochkarev³

et al.

Abstract: The article presents epidemiological data, age-related characteristics of hair and scalp diseases in children, and presents clinical cases with typical and rare dermatoses of this localization.

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Structural and functional characteristic of thyroid gland in children and adolescents with alopecia areata by data of laboratory and ultrasound examination

Shtina,

Ustinova,

Zenina

et al. 2024

Rus. J. Clin. Derma. Vener.

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Structural and functional characteristic of thyroid gland in children and adolescents with alopecia areata by data of laboratory and ultrasound examination

Shtina,

Ustinova,

Zenina

et al. 2024

Rus. J. Clin. Derma. Vener.

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Norovirus Infection in the Sverdlovsk Region, 2009–2022: Retrospective Epidemiological Analysis and Statistical Modeling Results

Chalapa,

Kosova,

Mashin

et al. 2023

PH&LE

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Introduction: Norovirus infection (NVI) is a highly contagious disease that is most common in children and entails significant health care costs. Objectives: To analyze and describe epidemic spread patterns of norovirus infection in the Sverdlovsk Region in 2009–2022 and to examine its determinants using statistical modeling techniques. Materials and methods: We have analyzed statistics on the monthly number of NVI cases and newborns, publicly available data on weather factors and population migration in the Sverdlovsk Region. Negative binomial regression was used to assess contribution of natural and social factors to disease incidence. The statistical analysis was carried out in the R environment. Results: A long-term increasing trend in NVI incidence that stabilized on a relatively high level in 2016–2018 was observed. The epidemic season usually started in October or November and lasted until April–May. Children under 6 years of age were at highest risk of the infection. Distribution of the disease incidence across the Sverdlovsk Region was uneven; relatively high rates were registered in some municipalities. The results of statistical modeling showed a negative correlation between weather conditions (mean temperature and relative humidity), high COVID-19 rates, and NVI incidence. The amount of precipitation, atmospheric pressure, sunshine duration, and external migration were found to be statistically insignificant predictors. In addition to the above, the level of herd immunity is likely to affect the NVI incidence, although it is hard to estimate the extent of its impact due to the lack of trustworthy data on the duration of immunity to noroviruses. Conclusion: Norovirus infection is a regional health care challenge, especially among preschool children. Ambient air temperature, relative humidity, and social distancing due to rising COVID-19 incidence rates proved to be negative predictors associated with a decrease in the number of NVI cases in the study area.

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Hair Loss (Alopecia) in Children: Etiology, Epidemiology, Clinical Characteristics, Differential Diagnosis

Abstract: The article presents epidemiological data, age-related characteristics of hair and scalp diseases in children, and presents clinical cases with typical and rare dermatoses of this localization.

Cited by 2 publications

References 0 publications

Structural and functional characteristic of thyroid gland in children and adolescents with alopecia areata by data of laboratory and ultrasound examination

Structural and functional characteristic of thyroid gland in children and adolescents with alopecia areata by data of laboratory and ultrasound examination

Norovirus Infection in the Sverdlovsk Region, 2009–2022: Retrospective Epidemiological Analysis and Statistical Modeling Results

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