From af5152beeee8bf7966f544ea7f434cbf9a25f411 Mon Sep 17 00:00:00 2001 From: Sebastian Funk Date: Wed, 28 Feb 2024 17:59:41 +0000 Subject: [PATCH] edit --- slides/mpi_goettingen_20240227.html | 304 ++++++++++++++-------------- 1 file changed, 152 insertions(+), 152 deletions(-) diff --git a/slides/mpi_goettingen_20240227.html b/slides/mpi_goettingen_20240227.html index b2d06f4..95a7dde 100644 --- a/slides/mpi_goettingen_20240227.html +++ b/slides/mpi_goettingen_20240227.html @@ -409,56 +409,56 @@
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Acknowledgements

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Acknowledgements

Former and current members of the EpiForecasts group (https://epiforecasts.io):
-Akira Endo, Alexis Robert, Ciara McCarthy, Hannah Choi,
-Hugo Gruson, James Azam, James Munday, Joel Hellewell,
-Joseph Palmer, Kath Sherratt, Liza Hadley, Manuel Stapper,
-Nikos Bosse, Robin Thompson, Sam Abbott, Sophie Meakin,
-Toshiaki Asakura


+Akira Endo, Alexis Robert, Ciara McCarthy, Friederike Becker,
+Hannah Choi, Hugo Gruson, James Azam, James Munday,
+Joel Hellewell, Joseph Palmer, Kath Sherratt, Liza Hadley,
+Manuel Stapper, Nikos Bosse, Robin Thompson, Sam Abbott,
+Sophie Meakin, Toshiaki Asakura


Collaborators at LSHTM and elsewhere.


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Models are a tool to combine data (what we know) with assumptions and theory (what we think) to learn about what we don’t know.

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When data is abundant, models and analytics can generate insight without many additional assumptions.

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When data is sparse (e.g. early in an outbreak), modellers need to make more assumptions to generate insights.

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January 2020: Can COVID-19 be controlled by contact tracing?

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Probability of control depends on intensity of transmission and contact tracing effort.

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“We illustrate the potential impact that flawed model inferences can have on public health policy with the model described […] by Joel Hellewell and colleagues, which is part of the scientific evidence informing the UK Government’s response to COVID-19.”

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“All models are wrong, but some are useful”

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“All models are wrong, but some are useful”

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The future as a (particular) data gap

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The future as a (particular) data gap

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The future as a (particular) data gap

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The future as a (particular) data gap

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Mechanistic models support causal understanding, but predictions can have value in their own right

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Mechanistic models support causal understanding, but predictions can have value in their own right

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Mechanistic models support causal understanding, but predict

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Short-term forecasts can inform decision making

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Forecasting Ebola

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Forecasting Ebola

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Ebola in West Africa, 2013-16

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Ebola in West Africa, 2013-16

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“We were losing ourselves in details […] all we needed to know is, are the number of cases rising, falling, or levelling off?”

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Forecasts can be assessed/validated

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Forecasts can be assessed/validated

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Forecasts can be assessed/validated

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Forecasting paradigm

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Forecasting paradigm

“maximise sharpness subject to calibration”

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Forecasting paradigm

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Ebola: how wrong were our models?

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Ebola: how wrong were our models?

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Ebola: how wrong were our models?

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Ebola forecasts could be trusted for up to 2 weeks

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Our Ebola forecasts could be trusted for up to 2 weeks

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Forecasting COVID-19

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Forecasting COVID-19

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Forecasting via the renewal equation

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Forecasting via the renewal equation

\begin{align} \textrm{New infections}~I(t) & = R_t \sum_{\tau} g_{\tau} I_{t-\tau}\\ @@ -792,10 +792,10 @@

Forecasting via the renewal equation

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Global COVID case forecasts via the renewal equation

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Global COVID case forecasts via the renewal equation

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Global COVID case forecasts via the renewal equation

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Forecasting to inform policy in the UK

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Forecasting to inform policy in the UK

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Forecasting to inform policy in the UK

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European COVID-19 Forecast Hub

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European COVID-19 Forecast Hub

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European COVID-19 Forecast Hub

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How good were COVID forecasts?

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How good were COVID forecasts?

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We can compare forecasts using
proper scoring rules \[\mathrm{CRPS}(F, x) = \mathbb{E}|X-x| - \frac{1}{2}\mathbb{E}|X-X'|\] @@ -900,10 +900,10 @@

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Median ensemble outperforms individual models

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Median ensemble outperforms individual models

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Median ensemble outperforms individual models

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We can compare forecasts using proper scoring rules \[\mathrm{CRPS}(F, x) = \mathbb{E}|X-x| - \frac{1}{2}\mathbb{E}|X-X'|\] @@ -925,10 +925,10 @@

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Absolute quality of forecasts #1: baseline models

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Absolute quality of forecasts #1: baseline models

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Absolute quality of forecasts #1: baseline models

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Absolute quality of forecasts #2: calibration

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Absolute quality of forecasts #2: calibration

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Absolute quality of forecasts #2: calibration

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What limits predictive ability?

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What limits predictive ability?

  1. Unpredictable human behaviour?
  2. Unpredictable pathogen biology?
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    What limits predictive ability?

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Unpredictable human behavoiur?

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Unpredictable human behavoiur?

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Unpredictable human behavoiur?

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Observed behaviour as predictor: improvement of forecasts, but only once age-specific reporting is taken into account.

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Unpredictable biology?

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Unpredictable biology?

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Unpredictable biology?

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Variants as predictor: improvements of forecasts during transitions

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Variants as predictor: improvements of forecasts during transitions

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Variants as predictor: improvements of forecasts during tran

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Bad models? Human vs. machine.

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Bad models? Human vs. machine.

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Bad models? Human vs. machine.

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Inherent limits?

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Inherent limits?

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Inherent limits?

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What can we conclude for the next pandemic?

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What can we conclude for the next pandemic?

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Summary

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Summary

  • Covid-19 forecasts have been relatively poor further than one or two generations ahead
  • Ensembles perform best, but can be difficult to interpret
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    Summary

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Open questions:

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Open questions:

  • Can predictive performance be improved?
  • Are we measuring predictive performance in the right way?
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    Open questions:

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Alternative ways of measuring predictive performance change the ranking of models.

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Forecasting and nowcasting remain relevant

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Forecasting and nowcasting remain relevant

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Forecasting and nowcasting remain relevant

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New initiatives

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New initiatives

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European respiratory hub

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European respiratory hub

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European respiratory hub

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Evaluating conditional forecasts (“scenarios”)

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Evaluating conditional forecasts (“scenarios”)

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Evaluating conditional forecasts (“scenarios”)

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We need collaborative efforts, using standardised datasets to compare methods and generating sustainable tools

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We need collaborative efforts, using standardised datasets to compare methods and generating sustainable tools

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“We were losing ourselves in details […] all we needed to know is, are the number of cases rising, falling or levelling off?”

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“We were losing ourselves in details […] all we needed to know is, are the number of cases rising, falling or levelling off?”

– Hans Rosling, Liberia, 2014

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“We were losing ourselves in details […] all we

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Slides at

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Slides at

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