Publications by authors named "M M Litvinova"
Aedes-borne diseases represent a major public health threat and mosquito control operations represent a key line of defense. Improving the real-time awareness of mosquito control authorities by providing reliable forecasts of the relative abundance of mosquito vectors could greatly enhance control efforts. To this aim, we developed an analytical tool that forecasts Aedes aegypti relative abundance 1 to 4 weeks ahead.
View Article and Find Full Text PDFAim: To analyze associations between clinical and morphological features of kidney involvement in patients with systemic lupus erythematosus.
Materials And Methods: In the retrospective cohort study, we enrolled adult (≥18 years) patients with morphologically proven lupus nephritis (LN) stratified according to the ISN/RPS classification. Systemic lupus erythematosus was classified in accordance with ACR/EULAR classification criteria (2019).
Article Synopsis
- Accurate forecasts improve public health responses to seasonal influenza, with 26 teams providing predictions for hospital admissions in 2021-22 and 2022-23.
- Six out of 23 models performed better than the baseline in 2021-22, while 12 out of 18 models did so in 2022-23, with the FluSight ensemble being highly ranked in both seasons.
- Despite its accuracy, the FluSight ensemble and other models struggled with longer forecast periods, especially during times of rapid change in influenza patterns.
Background: Human contact patterns are a key determinant driving the spread of respiratory infectious diseases. However, the relationship between contact patterns and seasonality as well as their possible association with the seasonality of respiratory diseases is yet to be clarified.
Methods: We investigated the association between temperature and human contact patterns using data collected through a cross-sectional diary-based contact survey in Shanghai, China, between December 24, 2017, and May 30, 2018.
Accurate forecasts can enable more effective public health responses during seasonal influenza epidemics. Forecasting teams were asked to provide national and jurisdiction-specific probabilistic predictions of weekly confirmed influenza hospital admissions for one through four weeks ahead for the 2021-22 and 2022-23 influenza seasons. Across both seasons, 26 teams submitted forecasts, with the submitting teams varying between seasons.
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