Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


10.19191/EP20.5-6.S2.110

http://scihub22266oqcxt.onion/10.19191/EP20.5-6.S2.110
suck pdf from google scholar
33412802!ä!33412802

suck abstract from ncbi


Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534
pmid33412802      Epidemiol+Prev 2020 ; 44 (5-6 Suppl 2): 120-127
Nephropedia Template TP

gab.com Text

Twit Text FOAVip

Twit Text #

English Wikipedia


  • Analisi e previsioni dell'epidemia da SARS-CoV-2 in Toscana #MMPMID33412802
  • Cereda G; Viscardi C; Gottard A; Mealli F; Baccini M
  • Epidemiol Prev 2020[Sep]; 44 (5-6 Suppl 2): 120-127 PMID33412802show ga
  • OBJECTIVES: about two months after the end of the lockdown imposed for the containment of the SARS-CoV-2 epidemic, the contagion dynamics in the Tuscany Region (Central Italy) have been assessed from the beginning of the emergency to the end of June through a compartmental model, and future medium-long term projections have been produced. DATA AND METHODS: this study used a SIRD model in which the infection reproduction number R0 varied over time, according to a piecewise constant function. The fatality parameter and the time from contagion to infection resolution (death or recovery) were fixed to ensure parameter identifiability, and the model was calibrated on the Covid-19 deaths notified from March 9th to June 30th 2020. The uncertainty around the estimates was quantified through parametric bootstrap. Finally, the resulting model was used to produce medium-long term projections of the epidemic dynamics. RESULTS: the date of the first infection in Tuscany was estimated as February 21st 2020. The value of R0(t) ranged from 7.78 (95%CI 7.55-7.89), at the beginning of the outbreak, to a value very close to 0 between April 27th and May 17th. Finally, R0(t) rose, reaching an average of 0.66 (0.32, 0.88) between May 18th and June 30th. At the epidemic peak, estimated at the beginning of April, the notified infected people circulating in the region were just 22% of those predicted by the model. According to the estimated SIRD, under the hypothetical scenario that R0(t) slightly exceeds 1 from the beginning of October 2020, a new wave of contagion could arise by next spring. CONCLUSIONS: the estimated trend of R0(t) is suggestive of a strong effect of the lockdown in Tuscany and of a mild increase of the contagion potentially attributable to the easing of the containment measures. Medium-long term projections unequivocally indicate that the danger of a new epidemic wave has not been averted.
  • |*Forecasting[MESH]
  • |*Models, Theoretical[MESH]
  • |*Pandemics[MESH]
  • |*SARS-CoV-2[MESH]
  • |Basic Reproduction Number[MESH]
  • |COVID-19/*epidemiology/prevention & control/therapy[MESH]
  • |Humans[MESH]
  • |Italy/epidemiology[MESH]
  • |Mortality/trends[MESH]
  • |Quarantine[MESH]
  • |Seasons[MESH]


  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    Linkout box