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Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1932 1
1940 1
1942 1
1943 1
1944 1
1945 1
1946 14
1947 13
1948 10
1949 15
1950 13
1951 11
1952 22
1953 16
1954 25
1955 43
1956 19
1957 13
1958 18
1959 14
1960 14
1961 20
1962 22
1963 38
1964 25
1965 24
1966 36
1967 66
1968 70
1969 51
1970 87
1971 73
1972 83
1973 53
1974 81
1975 123
1976 143
1977 168
1978 212
1979 307
1980 306
1981 321
1982 433
1983 461
1984 530
1985 605
1986 603
1987 608
1988 833
1989 1009
1990 1232
1991 1248
1992 1316
1993 1480
1994 1619
1995 1782
1996 1953
1997 2211
1998 2328
1999 2524
2000 2750
2001 3193
2002 3500
2003 3672
2004 4038
2005 4386
2006 4901
2007 5511
2008 5883
2009 6089
2010 6577
2011 7320
2012 7921
2013 8647
2014 9356
2015 9732
2016 9985
2017 10609
2018 11695
2019 12317
2020 14097
2021 12866
2022 9864
2023 9405
2024 5388

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194,782 results

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Page 1
Improving probabilistic infectious disease forecasting through coherence.
Gibson GC, Moran KR, Reich NG, Osthus D. Gibson GC, et al. PLoS Comput Biol. 2021 Jan 6;17(1):e1007623. doi: 10.1371/journal.pcbi.1007623. eCollection 2021 Jan. PLoS Comput Biol. 2021. PMID: 33406068 Free PMC article.
Centers for Disease Control and Prevention (CDC) runs a challenge for forecasting weighted influenza-like illness (wILI) at the national and regional level. ...Enforcing probabilistic coherence led to an increase in forecast skill for 79% of the models we tes …
Centers for Disease Control and Prevention (CDC) runs a challenge for forecasting weighted influenza-like illness (wILI) at th …
Forecasting Risk of Crop Disease with Anomaly Detection Algorithms.
Skelsey P. Skelsey P. Phytopathology. 2021 Feb;111(2):321-332. doi: 10.1094/PHYTO-05-20-0185-R. Epub 2021 Jan 13. Phytopathology. 2021. PMID: 32748734 Free article.
In many cases, however, only information on outbreaks is collected and data from surrounding healthy crops are omitted. Use of such data to develop models that can forecast risk/no risk of disease is therefore problematic, as information relating to the no-risk stat …
In many cases, however, only information on outbreaks is collected and data from surrounding healthy crops are omitted. Use of such data to …
Multiscale influenza forecasting.
Osthus D, Moran KR. Osthus D, et al. Nat Commun. 2021 May 20;12(1):2991. doi: 10.1038/s41467-021-23234-5. Nat Commun. 2021. PMID: 34016992 Free PMC article.
Dante outperformed DBM for nearly all spatial units, flu seasons, geographic scales, and forecasting targets. Dante's sharper and more accurate forecasts also suggest greater public health utility. ...The methodology underpinning Dante can be used in other seasonal …
Dante outperformed DBM for nearly all spatial units, flu seasons, geographic scales, and forecasting targets. Dante's sharper and mor …
Fertility, mortality, migration, and population scenarios for 195 countries and territories from 2017 to 2100: a forecasting analysis for the Global Burden of Disease Study.
Vollset SE, Goren E, Yuan CW, Cao J, Smith AE, Hsiao T, Bisignano C, Azhar GS, Castro E, Chalek J, Dolgert AJ, Frank T, Fukutaki K, Hay SI, Lozano R, Mokdad AH, Nandakumar V, Pierce M, Pletcher M, Robalik T, Steuben KM, Wunrow HY, Zlavog BS, Murray CJL. Vollset SE, et al. Lancet. 2020 Oct 17;396(10258):1285-1306. doi: 10.1016/S0140-6736(20)30677-2. Epub 2020 Jul 14. Lancet. 2020. PMID: 32679112 Free PMC article.
Findings also suggest a shifting age structure in many parts of the world, with 2.37 billion (1.91-2.87) individuals older than 65 years and 1.70 billion (1.11-2.81) individuals younger than 20 years, forecasted globally in 2100. By 2050, 151 countries were forecasted …
Findings also suggest a shifting age structure in many parts of the world, with 2.37 billion (1.91-2.87) individuals older than 65 years and …
Forecasting life expectancy, years of life lost, and all-cause and cause-specific mortality for 250 causes of death: reference and alternative scenarios for 2016-40 for 195 countries and territories.
Foreman KJ, Marquez N, Dolgert A, Fukutaki K, Fullman N, McGaughey M, Pletcher MA, Smith AE, Tang K, Yuan CW, Brown JC, Friedman J, He J, Heuton KR, Holmberg M, Patel DJ, Reidy P, Carter A, Cercy K, Chapin A, Douwes-Schultz D, Frank T, Goettsch F, Liu PY, Nandakumar V, Reitsma MB, Reuter V, Sadat N, Sorensen RJD, Srinivasan V, Updike RL, York H, Lopez AD, Lozano R, Lim SS, Mokdad AH, Vollset SE, Murray CJL. Foreman KJ, et al. Lancet. 2018 Nov 10;392(10159):2052-2090. doi: 10.1016/S0140-6736(18)31694-5. Epub 2018 Oct 16. Lancet. 2018. PMID: 30340847 Free PMC article.
We assessed the performance by fitting models with data from 1990-2006 and using these to forecast for 2007-16. Our final model used for generating forecasts and alternative scenarios was fitted to data from 1990-2016. ...At the same time, Central African Republic, …
We assessed the performance by fitting models with data from 1990-2006 and using these to forecast for 2007-16. Our final model used …
Using prediction polling to harness collective intelligence for disease forecasting.
Sell TK, Warmbrod KL, Watson C, Trotochaud M, Martin E, Ravi SJ, Balick M, Servan-Schreiber E. Sell TK, et al. BMC Public Health. 2021 Nov 20;21(1):2132. doi: 10.1186/s12889-021-12083-y. BMC Public Health. 2021. PMID: 34801014 Free PMC article.
METHODS: We report the results of the first large-scale, long-term experiment in crowd-forecasting of infectious-disease outbreaks, where a total of 562 volunteer participants competed over 15 months to make forecasts on 61 questions with a total of 217 possi …
METHODS: We report the results of the first large-scale, long-term experiment in crowd-forecasting of infectious-disease outbr …
Forecasting the final disease size: comparing calibrations of Bertalanffy-Putter models.
Brunner N, Kühleitner M. Brunner N, et al. Epidemiol Infect. 2020 Dec 28;149:e6. doi: 10.1017/S0950268820003039. Epidemiol Infect. 2020. PMID: 33357248 Free PMC article.
Using monthly data from the Ebola-outbreak 2013-2016 in West Africa, we compared two calibrations for data fitting, least-squares (SSE) and weighted least-squares (SWSE) with weights reciprocal to the number of new infections. To compare (in hindsight) forecasts for the fi …
Using monthly data from the Ebola-outbreak 2013-2016 in West Africa, we compared two calibrations for data fitting, least-squares (SSE) and …
Applying infectious disease forecasting to public health: a path forward using influenza forecasting examples.
Lutz CS, Huynh MP, Schroeder M, Anyatonwu S, Dahlgren FS, Danyluk G, Fernandez D, Greene SK, Kipshidze N, Liu L, Mgbere O, McHugh LA, Myers JF, Siniscalchi A, Sullivan AD, West N, Johansson MA, Biggerstaff M. Lutz CS, et al. BMC Public Health. 2019 Dec 10;19(1):1659. doi: 10.1186/s12889-019-7966-8. BMC Public Health. 2019. PMID: 31823751 Free PMC article.
Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization forecasts, as well as other infectious diseases. Using CDC influenza forecasting challenges as an example, this paper provi …
Additional efforts to advance forecasting science have included influenza initiatives focused on state-level and hospitalization f …
Forecasting viral disease outbreaks at the farm-level for commercial sow farms in the U.S.
Paploski IAD, Bhojwani RK, Sanhueza JM, Corzo CA, VanderWaal K. Paploski IAD, et al. Prev Vet Med. 2021 Nov;196:105449. doi: 10.1016/j.prevetmed.2021.105449. Epub 2021 Jul 29. Prev Vet Med. 2021. PMID: 34376325
Overall accuracy was 99.3 %, although this metric is heavily biased by imbalance in the data (less than 0.7 % of farms had an outbreak each week). This platform has been used to deliver weekly real-time forecasts since December 2019. The forecast platform has a buil …
Overall accuracy was 99.3 %, although this metric is heavily biased by imbalance in the data (less than 0.7 % of farms had an outbreak each …
Daily Forecasting of Regional Epidemics of Coronavirus Disease with Bayesian Uncertainty Quantification, United States.
Lin YT, Neumann J, Miller EF, Posner RG, Mallela A, Safta C, Ray J, Thakur G, Chinthavali S, Hlavacek WS. Lin YT, et al. Emerg Infect Dis. 2021;27(3):767-778. doi: 10.3201/eid2703.203364. Emerg Infect Dis. 2021. PMID: 33622460 Free PMC article.
To increase situational awareness and support evidence-based policymaking, we formulated a mathematical model for coronavirus disease transmission within a regional population. This compartmental model accounts for quarantine, self-isolation, social distancing, a nonexpone …
To increase situational awareness and support evidence-based policymaking, we formulated a mathematical model for coronavirus disease …
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