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Community Ebola Modeling Phone Call

Revision as of 13:08, 26 January 2015 by Judyvdouglas.verizon.net (Talk | contribs) (Agenda)

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Contents


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The STEM Community is holding a weekly phone call for open discussion on Ebola Modeling. Researchers studying Ebola Epidemiology, Modeling, and working on Ebola Response, are all invited. Our goal is to accelerate research by helping members of the scientific community interact, share data, questions, and ideas with each other, and to connect researchers with operational people. It is not necessary or required to be a user or contributor to STEM. All discussion should be open and non-confidential.

The Ebola community call is scheduled to take place most every Weds at 11AM Pacific Daylight time (2PM Eastern Time)

Join the Community Call

For more information, to add to the agenda, or if you wish to join, please send mailto:judyvdouglas@verizon.net

Participants

List of all current and previous Ebola Call Participants

January 28, 2015 Call

Phone call will begin at 2PM Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for January 28th

Moderator: Simone Bianco, IBM Research - Almaden

  1. Welcome and Introductions
  2. News
  3. Items from Participants
  4. Deep Dive Talk: Simone Bianco, IBM Research - Almaden, will summarize the workshop hosted by Georgia Tech last week
  5. Planning
    1. Who would like to moderate future meetings?
    2. What will be the deep dive topic?
    3. Please send brief items for the agenda to judyvdouglas@verizon.net
    4. Please suggest other themes and guests for presentation/discussion
    5. Future calls
      1. February 4: Volunteers?
      2. February 11: Volunteers?

Minutes

Attendees
Welcome and Introductions
Discussion
Planning Future Meetings

January 21, 2015 Call

Phone call will begin at 2PM Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for January 21st

Moderator: Kun (Maggie) Hu, IBM Almaden

  1. Welcome and Introductions
  2. News
  3. Items from Participants
  4. Deep Dive Talk: Kun Hu, IBM Research - Almaden, will report on IBM Open Data Jam project and event.[1]
  5. Planning
    1. Who would like to moderate future meetings?
    2. What will be the deep dive topic?
    3. Please send brief items for the agenda to judyvdouglas@verizon.net
    4. Please suggest other themes and guests for presentation/discussion
    5. Future calls
      1. January 28: Simone Bianco will present the deep dive (tentative)
      2. February 4: Volunteers?

Minutes

Attendees
  1. Kun Hu, IBM Almaden
  2. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
  3. Judy Douglas, IBM Almaden
  4. Stefan Edlund, IBM Almaden
  5. Bill Tetzlaff, IBM Watson
  6. Ilan Rubin, Georgia Tech (visiting from Cornell)
  7. Joshua Weitz, Georgia Tech
Welcome and Introductions

New to call: Ilan Rubin, a student (from Cornell) who is working with Dr. Weitz’s group on Ebola modeling at Georgia Tech; Dr. Weitz, who was busy preparing for tomorrow’s workshop, also joined the call during Kun’s presentation. Dr. Weitz’s team is doing work on contact tracing, post-death transmission, calculation of the Ro, etc.

Kun: Call will be short today; Simone Bianco traveling to Georgia for workshop where he will present a poster on work with US Navy Research Lab on contact tracing;

Discussion

Kun: Last year CDC predicted 1.4 million cases by this January; now have 21,000. Good news—but the impact on the economy has been negative, with food security problems arising because people are afraid to go to the market. Farmers haven’t been able to sell their products.

Bill: Interview on Politico with the man appointed the US Ebola czar who has now stepped down. His task was political—he worked to reassure the US population and coordinate US military and health workers. US Governmental interest is now at a low level.

Bill: After Hurricane Sandy, a project at Watson focused on coordinating different groups bringing relief; smartphone based, ad hoc support for data and communications

Kun: This project was represented at the IBM internal meeting last week

Kun: Modeler and scientist have to have reliable data to produce validated model for scenario test and prediction; the Open Data Jam is addressing this with a website listing public available datasets; will have Ebola Open Data Jam II in various places in February; is open to public.


Planning Future Meetings

Joshua: He will exchange emails with Kun, look at possible topics for February 4th or after

Bill: Possible topic might be titled “The Proper Place for Ebola Modeling”; data used in early models “flaky”, need to get data on the group, evaluate effects of different types of remediation

January 14, 2015 Call

Phone call will begin at 2PM Eastern Standard Time (11AM Pacific Standard Time)

Agenda

"for" January 14

Moderator: Stefan Edlund, IBM Research, Almaden (Simone will be at a meeting)

  1. Welcome and introductions
  2. News
  3. Items from participants
  4. Deep dive talk: Alex J. Jones, Operon Labs, will talk on new diagnostics on the market
  5. Planning 2015's agenda
    1. Who would like to moderate?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future calls
      1. January 21, TBD
      2. January 28, TBD

Minutes

Attendees
  1. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
  2. Richard Stovkis, Chief Medical Officer of Cures United
  3. Judy Douglas, IBM Almaden
  4. Stefan Edlund, IBM Almaden
  5. Michael Perrone, IBM Watson
  6. Bill Tetzlaff, IBM Watson
  7. Alexander J. Jones, OperonLabs, NIH
  8. Alexe Bojovschi, IBM Research, Australia
Discussion

News/Items from participants Judy: China sending large Ebola relief team to West Africa – Associated Press

Sheldon: Situation worsening in Sierra Leone, now at 50 cases/day; Liberia at 20/day, Guinea at 4/day. Country population: Sierra Leone 6 million, Liberia 2.5 million, Guinea 12 million

Alex: Sierra Leone is where Liberia was in October; media frenzy in US down, issue seems to have fallen off Americans’ radar screen

Richard: “Still a mess“ in Sierra Leone; reported cases vary dramatically day-to-day

Michael: 4 hour meeting on Ebola yesterday at Yorktown to brainstorm solutions, corporate strategies; attendees from across IBM, including Kenya; two from DoD; resources are available

Michael: Wants to bring different groups together, will send Judy his lists

Bill: As long time emeritus IBM researcher, knows how IBM supports efforts, also knows people in the company; need isn’t for high-tech apps

Stefan: Focus of these calls is on modeling

Michael: Can give names of those attending his groups who have an interest in modeling

Alex: Would join another group

Bill: Would serve as bridge between Yorktown and Almaden groups

Discussion: Sierra Leone has old mobile phones, good network; but not smart phones (for data); free texting is being used to track disease, e.g., “my husband has symptoms”

Deep Dive talk

Alexander J. Jones, OperonLabs on Diagnostic and Ebola. Presentation available in agenda.

Richard: Lots of mucosal involvement in Ebola; if catch in first 3 days, not so bad; knowing viral load might be helpful

Discussion: Lack of FDA approval for RT-PCR devices; off label use of FDA approved drugs with known risk; seemingly a problem in Africa, but not in US or Europe

Richard: We’re where we were with HIV/AIDS 10-20 years ago

Richard & Alex: Approval process is a stumbling block; shouldn’t wait; question in years ahead will be why didn’t we treat earlier, why did we let so many people die?

Richard: His team will use Q-RT-PCR machines

Alex: Collecting data from the RT-PCR machines could be valuable; comparison of viral loads on different days might help treatment, epidemiological modeling, decisions in the field

Alex is currently visiting a company building an open source Q-RT-PCR in the bay area.

Planning
  1. No volunteers at this time
  2. Tentative schedule: Kun on January 21, on Yorktown meeting; Simone on January 28

Jan 7, 2015 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for Jan 7

Moderator: Kun (Maggie) Hu, IBM Research, Almaden

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. Deep dive talk: "Passenger Screening for Ebola: The New Security or the New Threat?" Presented by Prof. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
  5. Planning 2015's agenda
    1. Who would like to moderate in Jan 2015?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future Calls:
      1. Jan. 14, TBD
      2. Jan. 21, TBD

Minutes

Attendees
  1. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
  2. Richard Stovkis, Chief Medical Officer of Cures United
  3. Judy Douglas, IBM Almaden
  4. Leah Shaw, William and Mary
  5. Simone Bianco, IBM Almaden
  6. Stefan Edlund, IBM Almaden
  7. James Kaufman, IBM Almaden
  8. Kun (Maggie) Hu, IBM Almaden
  9. Michael Perrone, IBM Watson
  10. Bill Tetzlaff, IBM Watson
  11. Alexander J. Jones, OperonLabs, NIH
Discussion

Kun (Maggie): Welcome to the first call of 2015, and thanks to all for last year’s participation

Michael Perrone: New to call, from IBM Research Yorktown, was in Ebola jam last October, has been working on Ebola app with a group there since then, would like to get them involved with the Modeling call

Other potential new participants: Meenal Pore (she’s 8 hours ahead of us) from IBM Africa Research Lab, also China CDC Vice General Director (it’s 3 am there)

Simone: Workshop January 22-23, Modeling Spread and Control of Ebola in West Africa, at Georgia Tech, [2]. Will give report on workshop as Deep Dive the following week, January 28

Kun: China CDC Director wants to join in call; need to work on a time he can do so

Richard: Making slow but steady progress, will start intervention in Sierra Leone in February; will talk with Kun following the call re their shared modeling effort, items not yet ready for dissemination


Deep Dive talk

Prof. Sheldon Jacobson’s presentation: Passenger Screening for Ebola: The New Security or the New Threat; powerpoint available in agenda.

Query: Why no actual blood screening at airports? Seems to be only test that’s reliable

Answer (Sheldon): Doesn’t know reason why

Query (Simone): Any resources being shifted from security to Ebola?

Answer (Sheldon): Thinks not, but don’t have evidence

Discussion: Cost of treatment lower with testing due to earlier diagnosis, also cost in US $0.5-1 Million, in West Africa $2K

Bill T: Most leaving are aid workers, need to offer those tested treatment, evacuation to Europe or US

Alex: Blood test reliable only if close to coming down with the disease; other tests not reliable; genetics are involved

James: 2 ways to think about screening: (1) to ID those who are sick and keep from traveling or (2) to track and help (contact tracing, treatment)

Sheldon: Yes, need to clarify the objective; exit screening is critical

Alex: The greater the number of people with the disease, the greater the chance the virus will adapt

Sheldon: Yes, compare with Spanish flu

Alex: Disease shows wave pattern; emergent behavior; West Africa borders are artificial, with different ethnic groups

Planning
  1. January 14: Alex will moderate, give Deep Dive on new diagnostics on the market
  2. January 21: Kun (Tentative, Deep Dive report on meeting she’s attending in New York next week; to be confirmed)
  3. January 28: Simone to give Deep Dive on Georgia Tech workshop
  4. Kun will write Director of China CDC to invite him to give a talk; will give alternate dates, ask what time works for him

December 17, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for December 17

Moderator: Kun (Maggie) Hu, IBM Research, Almaden

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. Planning 2015's agenda
    1. Who would like to moderate in 2015?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future Calls:
      1. Jan. 7, Prof. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
      2. Jan. 14, TBD

Minutes

Attendees
  1. Kun (Maggie) Hu, IBM Research, Almaden
  2. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
  3. Bill Tetzlaff, IBM Watson
  4. Judy Douglas, IBM Research, Almaden
  5. Richard Stovkis, Chief Medical Officer of Cures United
  6. Roslyn Hickson, IBM Australia
  7. Alexe Bojovschi, IBM Research, Australia
  8. Alexander J. Jones, OperonLabs
Discussion

Welcome and Introductions Alexe Bojovschi, IBM Australia, new to call; PhD in molecular biology, working on computation aspect of Ebola, possibility of modeling the virus and how it inserts into cell

Open Discussion (no Deep Dive) Bill: Report in yesterday’s New York Times suggested that the rate of unreported Ebola may lower than previously estimated, perhaps half of what it was thought to be

Kun: Other news story suggested cases not report, bodies not claimed at a diamond mine in Sierra Leone

Richard: Huge differences in un-reporting between the 3 countries; Sierra Leone probably highest

Bill: CNN show on “ordinary heroes” reported on nursing student in Liberia who treated her family, saved 3 of 4 members, using some drugs and improvised equipment

Richard: Most patients in US survived if they got early treatment

Bill: Cases in CNN story suggest an intermediate data point

Alex (US): Most recent data points suggest rates going down: Liberia 16/day, Guinea, 23.5/day (with slow increasing rate), Sierra Leone 60/day

Richard: Situation in Sierra Leone hasn’t improved much; reporting may be bad; WHO gets data from ministries of health in Sierra Leone; 11-12 December 100 cases, 13 December 40, 14 December 4 0, 15 December 64, 16 December none reported, 17 December 55; some days missing, wide fluctuation

Bill: Nature of reporting—don’t really know

Alex (US): Have found Ebola virus in guinea pig genome, could be 60 million years old, or the estimate could be way off; looking for ancestor of protein; genetic archeology, fossilized genes; also in bats, one marsupial, etc.; Ebola and other pathogens not particularly lethal except in humans

Richard: True of Marburg virus as well; also bats no much affected; if intervention starts early enough, survival goes way up; children have best chance; age group a factor as in Spanish flu, difference in host response

Alex (US): Compare Ebola and avian flu—class 1 fusion, same form of fusion protein

Richard: Published work of Steven Opel @ Brown, other scientist @ UVA on host response, Ebola and flu

Alex (US): Host response modification, calcium entry blockers may prevent penetration of Ebola virus into cell; possibly testing of various medications affect on Ebola; may affect proteins molecular docking

Alexe (Australia): Also electrolytes stop entry...

Alex (US): Studying protein folding would be of interest; better software now than 10 years ago

Richard: Try to deal with this outbreak now, do other things later (remember last May when the outbreak was thought to be over); issues with approval process and prescribing off label


Deep Dive talk

None scheduled for this week.


Planning
  1. January 7: Professor Jacboson
  2. January 14: SEND SUGGESTIONS TO KUN, JUDY
  3. Roslyn: May be able to share in February, after confidentiality restrictions are lifted

December 10, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for December 10

Moderator: Richard Stovkis, Chief Medical Officer of Cures United

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. Simone Bianco from IBM research will share his latest trip to D.C. for 2 conferences/panels
    1. Responding to Global Health Crises – Technology & Policy Innovation. Organized by ITI and Intel
    2. Ebola: Meet the experts - A reverse procurement launch. Organized by the Corporate Council on Africa and the House Committee on Foreign Affairs
  5. Planning Next week's agenda
    1. Who would like to moderate in Jan 2015?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future Calls:
      1. Dec. 17, Mehmet H Gunes, title pending
      2. Jan. 7, TBD

Minutes

Attendees
  1. Kun (Maggie) Hu, IBM Almaden
  2. Judy Douglas, IBM Almaden
  3. Stefan Edlund, IBM Almaden
  4. Simone Bianco, IBM Almaden
  5. Melissa Cefkin, IBM Almaden
  6. Richard Stovkis, Chief Medical Officer of Cures United
  7. Bill Tetzlaff, IBM Watson
  8. Ada Yan, Univ of Melbourne
  9. Alexander J. Jones, OperonLabs, NIH


Discussion

Alex: Situation stabilized in Liberia at 10 new cases a day; situation deteriorating in Sierra Leone, moving up from 10 to 100 new cases a day; junior doctors are on strike.

Richard: Seems to be moving west in Sierra Leone.

Alex: Read that 70% of infections com from funerals.

Richard: Funeral rituals in Sierra Leone have not changed much, but the 70% is questionable.

Richard: Not enough beds in Sierra Leone; people not admitted into hospital get no treatment, need to go out and get food, fuel transmission; also, raining season is over so people move around more.

Alex: Outbreak in Liberia has moved back out from city to country at 10 new cases a day.

Kun: Panelist mentioned travel very difficult in Sierra Leone—what does that mean for Richard’s mobile lab?

Richard: Roads are like “trails,” sometimes have to walk to remote villages but majority of people reachable by road if you have 4 wheel drive; basically the more mobile labs you have, the more patients you can reach.

Richard: Plan to reach 90-95% in new year, compared to 20% now.

Alex: Read doing lockdowns in Sierra Leone; the striking junior docs want access to western medical care.

Richard: British and American run army hospitals have 40% mortality; other treatment centers have 70% (no hydration, not drugs); 40% still far too high; only 3 deaths among patients treated in US and Europe.

Richard: Only getting snippets of information on what treatment people get.

Bill: Who is staffing US and British hospitals? Richard: Army docs and nurses.

Richard: Quality still not high enough; we don’t supply enough drugs, etc. at the moment.

Alex: Number of cases now probably 2 times what’s report—but still below number modeled in September.


Deep Dive talk

Simone Bianco, Report on two panels he attended last week in Washington DC, one sponsored by the House Committee on Foreign Affairs, the other by the IT Council and Intel

Focus: What is the role of technology in this crisis

Panel 1: Attendees a mix of doctors, nurses from on the ground, plus representative of the modeling and scientific communities; plus US government officials (White House advisor, etc.)

USAID official: Now that the number of new cases in Liberia is below 10, need to shift from intervening to sustaining the effort

Take-away: There is a disconnect between what people do in the tech field and what is happening on the ground; no middle ground; people on ground didn’t want iPads, they wanted bicycles

Challenge: Build bridge to transition from science to policy—but difficult to implement policy. Need to empower locals, general government; need to introduce ideas from basic science

Challenge: Policies require an understanding of what is actually going on from a sociological and anthropological point of view

Panel 2: Attendees from companies proposing technical devices to address epidemic, e.g., one company proposed medical probes, etc., small electronic devices that we don’t even have here in US hospitals

Take-away: Need to connect existing technologies to what’s actually happening. One government official just back from Sierra Leone showed his welcome home kit for self monitoring Can take a couple of weeks or up to a couple of months to use some devices, depending on medical expertise; more important to have docs on the ground than to have lots of fancy equipment

Problems with data collection—who do you report to? Data is being collected but getting harder and harder to get ahold of; US government is engaging in talks re data sharing with three of the affected countries

Richard: Where do you put the bar for treatment? A $3K probe for checking hydration works as well as a much more expensive device; need to have doc who can use; with early diagnosis and treatment, survival goes up, transmission goes down

Melissa: Structural considerations, not just behavioral ones; if basics are not there (and fancy stuff is), mistrust results

Simone: IBM Kenya Lab has system in Sierra Leone that allows people to call in (per Richard, almost everyone has a cell phone) to report a dead body, road block, etc.; people bombarded by public service announcements; messages have to be ones that people can relate to

Richard: Like response to HIV testing in Africa; don’t want to be tested if not offered something in return; don’t want diagnosis if it means they have to go to a treatment center where chances of survival are one in ten

Bill: Some estimate cost of putting in a $15K Ebola testing machine in Sierra Leone as high as $½ to 1M counting in cost of skilled technicians, assurances they will be evacuated if they become ill

Richard: Can’t just put diagnostic machines; need staff; highest cost (probably more than ½ of total) is cost of insurance for evacuation, life insurance, etc.; cost $2-3M to evacuate to US

PLANNING NEXT WEEK’S AGENDA"

Consensus: Will have call for discussion, no deep dive planned

Kun will moderate; this will be the last call in 2014; will resume with regular call on January 7, 2015

December 3, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for December 3

Moderator: Mary Helander, IBM

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. 20 minute deep dive topic: Richard Stovkis, Chief Medical Officer of Cures United on intervention, with Kun (Maggie) Hu, IBM, on "quick modeling" Ebola Early Diagnosis and Treatment Model
  5. Planning Next week's agenda
    1. Who would like to moderate in two weeks?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future Calls:
      1. Dec. 10, tbd (PLEASE SEND IDEAS TO JUDY DOUGLAS)
      2. Dec. 17, Mehmet H Gunes, title pending

Minutes

Attendees
  1. Kun (Maggie) Hu, IBM Almaden
  2. Judy Douglas, IBM Almaden
  3. Stefan Edlund, IBM Almaden
  4. Richard Stovkis, Chief Medical Officer of Cures United
  5. Bill Tetzlaff, IBM Research
  6. Ada Yan, Univ of Melbourne
  7. Roslyn Hickson, IBM Australia
  8. Mary Helander, IBM Watson
  9. Leah Shaw, William and Mary
  10. Sheldon Jacobson, Univ of Illinois Urbana-Champaign
Discussion

Mary: opened call; no new participants; group opted to move directly to deep dive (no news, no items from participants) Maggie (Kun): posted slides on wiki Richard: sent slides by email

Deep Dive talk

DEEP DIVE: Richard opened and closed; Maggie reviewed modeling in middle

Richard: his group will be on the ground in Sierra Leone in early January if funding will be available soon.

Richard: protective garb frightening to patients; suits shown in Berlin show healthcare professionals’ faces and can undergo chemical showers for more safety

Richard: diagnosis in first 3 days decreases mortality, decreases transmission (as shown in slide)

Bill: is it rational for a patient to decide to stay at home?

Richard: we don’t know, but do know patient could do better at home with meds

Richard: in US and EU all patients diagnosed and treated early survived

Richard: in intervention and treatment, small things make a difference, e.g., need potassium in hydration but potassium is not in standard hydration

Richard: antiviral “cocktails”

Richard: be agnostic, try both pre-exposure and post-exposure

Richard: don’t have a vaccine now, and vaccines difficult to distribute safely in Africa

Bill: New York Times article on treatment center (one nurse, ten patients, couldn’t do a lot); underscores need for trained people

Richard: will bring 120 people to Sierra Leone in January; interventions to include food packages for patients who stay at home

Richard: IBM Kenya working with mobile phones, 90 minutes to get a test result

Maggie: gave presentation on preliminary model in earlier call; has worked with Richard (slide 11) to include day of diagnosis as a compartment

Mary: how to know when person diagnosed?

Maggie: when symptoms first appear

Maggie: open sourced Ebola model on wiki can be used to model different interventions (e.g., social distancing such as airport travel restrictions)

Stefan: what is day zero in the simulation

Maggie: November 18, used CDC reported case data to initialize the simulation

Richard: believes his group can keep outbreak under control “quite rapidly” and have very few patients in 3 months; will use mobile diagnostics; won’t wait on vaccines

Bill: even with vaccine, healthcare workers will need protective gear; no vaccine 100%

Richard: no vaccine has 100% efficacy; hope to collect data in Sierra Leone to feed back into model

Bill: changing dynamics, parameters (gear, drug) can affect model

Maggie: with more data, can improve, extend model

Mary: thanks to speakers for informative, substantive talk!

PLANNING NEXT WEEK’S AGENDA"

Richard will moderate

Ada will check with colleagues and get back to Maggie

Richard: would like to hear from IBM Kenya

Maggie: would like to hear research questions from Ada’s group, possibly collaborate with them

Sheldon: may give deep dive in January, but cannot commit as of yet (not sure about time)

November 19, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for November 19

Moderator: Leah Shaw, College of William and Mary

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. 20 minute deep dive topic: Leah Shaw, College of William and Mary Impact of Exposed Compartment on Modeling Disease Dynamics
  5. Planning Next week's agenda
    1. Who would like to moderate in two weeks?
    2. What will be the deep dive topic?
    3. Please send short agenda items to judyvdouglas@verizon.net by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Future Calls:
      1. Nov. 26, THANKSGIVING HOLIDAY
      2. Dec. 3, tbd
      3. Dec. 10, tbd
      4. Dec. 17, Mehmet H Gunes, title pending

Minutes

Attendees
  1. Simone Bianco, IBM Research
  2. Richard Stovkis, Chief Medical Officer of Cures United
  3. Leah Shaw, William and Mary
  4. Ada Yan, Univ of Melbourne
  5. Judy Douglas, IBM Research
  6. Ira Schwartz, US Naval Research Lab
  7. Sheldon Jacobson, Univ of Illinois Urbana-Champaign     
  8. Tridane Abdessamad, UAE University
  9. Melissa Cefkin, IBM Research
  10. Bill Tetzlaff, IBM Research
  11. Mehmet Gunes, Univ Nevada Reno
Discussion

Bill Tetzlaff: Healthcare population size, articles suggest that Healthcare workers that become infected are those who work in regular healthcare, where the ebola patients come first. The workers that have contracted ebola in ebola clinics also work on general healthcare. In Liberia: 5M people, 5000 healthcare workers, 51 doctors (1 in 16 already infected). 1 in 2000 general population are infected with ebola. The medical staff are going to be decimated in the coming months. if model could be separated into 2 populations, crisis is for healthcare workers; focus on them might drive need for test kits

Simone: some models allow for separation. Kun has done some work here; and Simone are Kun are not the only ones to do so (but are the only ones to do spatially); it’s complicated. Tried to see effect of number of healthcare workers, size of population; haven’t seen data to show change; access to personal protective gear is better---has this had an impact?

Simone: Is there any trend in these two populations? Downward, upward, stable? Not much data is collected/shared

Richard: Many clinics are closed to prevent general access. Also 10% of patients with ebola have active malaria, and they have problem with false negatives and false positives.

Deep Dive talk

Leah Shaw, College of William and Mary Impact of Exposed Compartment on Modeling Disease Dynamics

Ordinary differential equations (ODE) vs. delayed differential equations (DDE), effect on modeling dynamics, parameter fittings, tried two different ways to write ODE models. Models were integrated in MatLab, deterministic model, numerical integration

Ada: how much contact tracking data? how many compartments? Using 1 exposed compartment and then go to more compartments by fitting the data, by including contact tracing data.

Leah: fixed latent vs. exponentially distributed Infectious period; implication-how long to monitory people

Leah: Look at Wearing paper on reproduction rate (cited on last slide)

Simone: SEIR with only one Exposed compartment? Reproductive number less than 2 underestimating?

Leah: Most using multiple I classes, only one E class

Simone: Any epidemiological basis that confirms E period?

Richard: some info, not much; depends on testing used (viral load?); no hard scientific evidence that people shed virus only after symptoms appear

Richard: Is it possible to do age stratification? It is possible to divide exposed in age groups, since age is an important component of the infection. The disease develops in younger people to a much higher chance of survival for people over 20.

Ada: Correct distribution in exposed is important. What effects would it have the impact of infections? Anything that interacts with time (like intervention on exposed) may be impacted on by this. How would this affect parameter fitting?

Sheldon: how would it affect prophylaxis, vaccination?

Leah: would like to talk more, work with those interested

November 12, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for November 12

Moderator: Dr. Melissa Cefkin IBM Research, Almaden

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. 20 minute deep dive topic: Some Insights from Anthropologists on Ebola
  5. Planning Next week's agenda
    1. Who would like to moderate in two weeks?
    2. What will be the deep dive topic?
    3. Please send short agenda items to jhkauf@us.ibm.com by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Next week's deep dive: Dr. Melissa Cefkin IBM Almaden. Topic "Some Insights from Anthropologists on Ebola"
    6. Future Calls:
      1. Nov. 19, moderator: Leah Shaw, College of William and Mary subject tbd
      2. Nov. 26, THANKSGIVING HOLIDAY
      3. Dec. 3, tbd
      4. Dec. 10, tbd
      5. Dec. 17, Mehmet H Gunes, title pending

Minutes

Attendees
  1. Sheldon Jacobsen, Dept of Computer Science, University of Illinois, Urbana
  2. James Kaufman
  3. Pat Selinger
  4. Melissa Cefkin
  5. Mary Helander December 3rd
  6. Richard Stokvis, Chief Medical Officer of Cures United, the Netherlands
  7. Simone Bianco
  8. Stefan Edlund
  9. Leah Shaw
  10. Nic Geard University of Melbourne
  11. Alexander J. Jones
  12. Michael Washington from CDC modeling Unit
  13. Mehmet Gunes
  14. Caitlin Rivers
  15. Bill Tetzlaff
Discussion

Alex: Total is 13594 confirmed cases. May underestimate by factor of 3.

5160 - 5400 Deaths Nurse died in Mali Imam died in Mali Africa Cup cancelled U.S. Nurses (Kaiser SF) on strike over Ebola measures and training Article on poverty and transmission, plan to model based on lights at night

Pat: Syndemics references could motivate new models.

Caitlin: WHO just posted new data portal

Alex: Question. Early in the outbreak we were able to rely on underreporting as constant rate or value. But it seems to be changing. Can we look at data to estimate changing rate of underreporting?

Deep Dive talk

Alex: JFK hospital referred to locally as "Just for Killing" even before Ebola

Richard: Half the people die in the modeling. What could be done when you treat people properly - how would it change the outcome and develop trust in the treatment centers? 400 nurses and doctors died because they did not have the required protected gear.

JK: How does treatment change mortality rate

Richard: Patient in Hamburg recovered. Patient in NY treatment not published yet successful treatments only partially published Consensus among infectious disease experts is that there is chance of recovery of 95% with proper treatment Statins and other drugs are thought to be quite effective. It's not just treating the virus but also treating the patient

Alex: Local practices that may even emerge from "Myths" sometimes lead to quarantine (not based on germ theory but still effective)

Bill T: Looked population statistics on health workers. modeling running out of health workers. We need numbers on health workers

Discussion between Alex and Richard on Melatonin: Richard indicates there may be >50 compounds that help. With proper treatment people survive. The doctors mix and match. A lot of things seem to work. We need to see more published protocols. Fujifilm offered compound T-705 (Avagan registered in Japan for Flu, stockpiled for flu) WHO is trying to decide if when we should do a clinical trial - it's sitting idle. With > 50% mortality don't need placebo controlled trials, just do something. In Africa the protective gear equipment is like "cardboard" compared to gear in the US (not possible to remove it without touching skin). PH affects weather the chlorine works. 400 workers die - most of them are locals. Treatment and equipment is not based on science.

10% of Ebola patients ALSO have active malaria. People with Malaria went for treatment and contracted Ebola in the clinic.

November 5, 2014 Call

Phone call will begin at 2pm Eastern Standard Time (11AM Pacific Standard Time)

Agenda

for November 5

Moderator: Dr. Emma McBryde University of Melbourne

  1. Welcome and Introductions
  2. News
  3. Items from participants
  4. 20 minute deep dive topic: Ebola Infectivity over time Presenter: Dr. Emma McBryde. Please click HERE for the slides
  5. Planning Next week's agenda
    1. Who would like to moderate in two weeks?
    2. What will be the deep dive topic?
    3. Please send short agenda items to Judy by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Next week's deep dive: Dr. Melissa Cefkin IBM Almaden. Topic "Some Insights from Anthropologists on Ebola"
    6. Next week's moderator: Melissa Cefkin IBM Almaden

Minutes

Attendees
  1. James Kaufman, IBM Almaden
  2. B.Tetzlaff, IBM Watson
  3. S.Bianco, IBM Almaden
  4. J. Douglas, IBM Almaden
  5. Jodie McVernon, University of Melbourne
  6. Kraig Butrum, Skoll Global
  7. Matt Davis, IBM Australia
  8. James Mccaw, University of Melbourne
  9. Stefan Edlund, IBM Almaden
  10. Ira Schwartz, US Naval Research Laboratory
  11. Emma McBryde, University of Melbourne
  12. Melissa Cefkin, IBM Almaden
  13. Kun Hu, IBM Almaden
  14. Alexander J. Jones, OperonLabs, NIH
  15. Leah Shaw, College of William and Mary
  16. Nic Geard, University of Melbourne
  17. Klimka Szwaykowska, US Naval Research Laboratory
  18. Pat Selinger, IBM Almaden
  19. Mehmet Gunes, University of Nevada, Reno
Discussion

News

B Tetzlaff: Read in Science health workers are still getting infected both in hazard suites but also in triage (without suits) Model does not segregate people who are with different risks. Can we extend model to distinguish clinical workers? Also people who are involved in burial, and friends and family in contact with sick family members outside of hospital

Emma: A number of people are thinking about how to model different risk groups. Alex: As model gets more complex have more granularity but sometimes data you feed the model is not available. Jamie: Agrees with Alex. Bill: Agrees....

Emma: All agree would be nice to have more model complexity but there are problems in doing that in particular finding appropriate parameters from the data and introducing unknown parameters. Word in newspapers is that things are slowing down in Liberia.

Alex: WHO gone from 3%/day increase to 1% but 2.5% factor under-reporting. Seems like a slowing in the rate of growth in Liberia Sierra Leone is accelerating. Difficult to separate out the noise. We really don't know and won't know for 1-2 months.

B Tetzlaff: Under-reporting is a guess and estimate is continuously changing.

Alex: If we take reports at face value there is a deceleration in Liberia and acceleration in Sierra Leon but we don't really know.

Emma: H Nishira did a model in Eurosurveilance looked at three countries as a system. R0 in Guinea<1 but for whole system R0 >1. This could happen again as various countries try to bring Ebola under control.

Alex: Rate accelerating in area around Freetown. Avg # daily cases is 6x higher than 2 months ago.

Deep Dive talk

Ebola Infectivity over time Presenter: Dr. Emma McBryde. Please click HERE for the slides

Infectiousness increases continuously over time from infectious onset to death slide 2 shows level in blood as fn of days after detection then drops off (for both fatal and nonfatal) Paper by Yemen and Galvani Anals of Internal Medicine. Oct 28th published online Example of a model that does microsimulations including infectivity by day Also looked at contacts drawn contract from a distribution. Assume same for everyone except during last stages of disease should we model change infection over time. If we want detail in interventions (eg training family for nursing at home) there is a delay between onset of fever and interventions - this should be captured in the model. showed how to extend the previous ebola model only additional parameters in this simple extension were transitions between infectious compartments. Three new transitions

Slide 7:

Q: Pat people die too early so peak happens too soon

E: That is correct. Slide 8 shows this

Patt: If we turn off hospitalization we would see this peak (breakdown in hospitalization)

Emma: Correct.

Alex: Useful to look at that.


The model results are very sensitive to assumptions around interventions on duration in the infectious compartment
Sensitivity extends to assumptions about shape of infectiousness and shape of interventions
These may need to be considered when thinking of interventions like home quarantine

Q from Simone: should we have fewer deaths from I1,I2 than I3,I4 how would that change the results ? Emma: Agree. Selecting from a parametric distribution of observed cases would give a more realistic model. The goal here was just to see if changing infectious changes the outcome of interventions. Lots of parameter changes would not matter much in this model but in reality might be very important. Starting from scratch want to use more realistic values in each compartment

Items from Participants

Item from Emma. Q for STEM people about issue of data sharing

Is creative commons ok for Eclipse.

Jamie: Probably it is. We just need to follow the submission process and Eclipse attorneys will review the license.

Jamie will update wiki on stochastic solvers

Leah Shaw will moderate in two weeks

October 29, 2014 Call

Phone call will begin at 2pm ET (11AM PDT)

Agenda

for October 29

Moderator: Simone Bianco, IBM Almaden Research Center

  1. Welcome and Introductions
  2. News
  3. Any follow-up items?
  4. Items from participants
  5. 20 minute deep dive topic: Modeling news on recent sensitivity analysis, SEIR++Parameters. Presenters: Kun Hu and Simone Bianco. Please click here for the slides [3]
  6. Next week's agenda
    1. Who would like to moderate in two weeks?
    2. What will be the deep dive topic?
    3. Please send short agenda items to Judy by Monday
    4. Please suggest other themes and guests for presentation/discussion
    5. Next week's deep dive: Dr. Emma McBryde, University of Melbourne. Topic to be announced
    6. Next week's moderator: Dr. Emma McBryde

Minutes

Attendees
  1. Simone Bianco (Moderator) IBM Almaden
  2. Dr Abdessamad Tridane for UAE University
  3. Ada Yan University of Melbourne
  4. Jodie McVernon, UoM
  5. Alexander J. Jones Operon Labs
  6. Lauren Barthel Operon Labs
  7. Ira B. Schwartz US Naval Research Laboratory
  8. Luis Mier-y-Teran John's Hopkins, NRL
  9. Klimka Szwaykowska US Naval Research Laboratory
  10. Emma McBryde University of Melbourne
  11. Bradford Green CDC Modeling Task force
  12. Mehmet Gunes, University of Nevada, Reno
  13. Nick Geard, University of Melbourne
  14. James Kaufman IBM Almaden
  15. Mary Roth IBM Almaden
  16. Melissa Cefkin IBM Almaden
  17. Kun Hu IBM Almaden
  18. Judy Douglas IBM Almaden
  19. Pat Selinger IBM Almaden
  20. Stefan Edlund IBM Almaden
  21. Bill Tetsloff IBM Watson
  22. Mary Helander IBM Watson
  23. Matthew Davis IBM Australia
  24. Rosalyn Hickson IBM Australia
Discussion

NEWS

Nick G: 2-year-old girl was sick on bus to Mali (now tracing 40+ contacts). She passed away.

Bill Tetsloff, NY, NY: People distrust information from CDC, etc.; are very afraid and need to be educated.

Alex (?): Lack of education in the media; cover is way to one side or the other. Becoming a political issue.

Judy: Woman taken to Maine will file suit tomorrow if they don't release her from quarantine.

Alex: Sent out public data sets on cell phone data. Most are private. Found one set with 146 people.


Deep Dive talk by Kun Hu and Simone Bianco

Kun and Simone presented STEM epidemiological model


Further Discussion

Emma: might find more uncertainty if use a different error function (binomial vs Poisson) Post mortem transmission rate is outside the literature range.

Kun: Yes, that's what our fit showed.

Alex: created a STEM model SEIR - model looks useful. NEJM paper has a weighted average for Ro from several models. comes up with 1.84. Q how Kun got Ro.

Kun Answer is: in the slides, expression for R0 + data in table.

Simone: C. Chavez, Vespignani and others have different values but all have R0<2.

Tridane: This model assumes everybody susceptible. Majority of ?happened at beginning of epidemic. Can you split S to those that work in Healthcare and those that do not. Many people do not go to hospital. Suggestion to split the susceptibles

Kun: Yes, one can split S into clinical workers and others. This could be a future extension to the model.

JK this would be particularly valuable if we could get statistics on clinical workers infected vs non-clinical. Otherwise it's easy to create the model but difficult to calibrate.

Emma: Epidemic peak time. Under any parameter that the epidemic had not peaked after 3 years

Kun: Not for these three countries. All the peaks times for three countries happen within 3 years.

Tridane: Do you plan to use model to examine efficiency of screening His group has model for vector born disease which shows difficulty of border screening

Kun: We've had this discussion during our call on Oct/15th. We've done some preliminary exploration and confirmed by participants from CDC during the call.

Alex great model but it is a limitation we don't have more data to seed the compartments especially burial rates

Simone burial rate is the most difficult to get. In SL if they suspect Ebola they have to report and then someone must come test body Very difficult to happen quickly. The delay is up to a week. Some people wait. Some people proceed with burial, some actually put bodies on street.

Items from Participants

Melissa will moderate and give deep dive in 2 weeks

Emma's topic for next week "has anybody mapped infectivity over time?"

Alex has paper about asymptomatic infectious over time

Tentative title "Ebola Infectivity over Time"

October 22, 2014 Call

Phone call will begin at 2pm ET (11AM PDT) to accommodate participants from Australia

Agenda

for October 22

Moderator: Ira B. Schwartz, US Naval Research Laboratory

  1. Welcome and Introductions
  2. News
  3. NIHR UK Follow-up: Asymptomatic carriers will pass through screening undetected
  4. Items from participants
  5. 20 minute deep dive topic: Adaptive human behavior to control epidemics Ira B. Schwartz, US Naval Research Laboratory. Please click here for the slides File:Ebola AN deep dive.pdf
  6. Next week's agenda
    1. Simone Bianco, IBM will moderate next week. Who would like to moderate in two weeks?
    2. Please send short agenda items to Judy by Monday
    3. Please suggest other themes and guests for presentation/discussion
    4. Next week's deep dive topic: Kun Hu & Simone Bianco model news on recent sensitivity analysis, SEIR++ Parameters
    5. Next week's moderator Simone Bianco
    6. In two weeks Dr. Emma McBryde, University of Melbourne will moderate and present Deep Dive next topic: "need title"

Minutes

Attendees
  1. Alexander J. Jones, OperonLabs
  2. Jamie Kaufman, IBM Research
  3. Ira Schwartz, US NRL
  4. Ada Yan, University of Melbourne
  5. Niina Haiminen, IBM Research
  6. Kun Hu, IBM Research
  7. Judy Douglas, IBM Research
  8. Matt Davis, IBM Research
  9. James McCaw, Melbourne School of Population and Global Health
  10. Leah Shaw, College of William and Mary
  11. Simone Bianco, IBM Research
  12. Pat Selinger, IBM Research
  13. Chang Chang, Peking University
  14. Melissa Cefkin, IBM Research
  15. Raul Andino, UC San Francisco
  16. Emma McBryde, University of Melbourne
  17. Nic Geard, University of Melbourne
Discussion

Jamie Kaufman: OperonLabs model contribution, to be contributed officially to Eclipse

Alex Jones, James McCaw, Jamie Kaufman: Need for an air travel model Adding escape rate with stability analysis of possible interest. There is a need to track people. US is enforcing travel restrictions to passengers from West African countries, to land in specific airports. Proposed joint collaboration to address air travel model.

Alex: Bats are a known reservoir. However, bats are not affected, just carriers, with mortality increasing upon transmission to human hosts. The reason why are bats not affected is still unknown. Bats are 30% of all mammals - why are they not affected by most virus? Bat interferon activates different genes. Interferon thought to be the link to an increased T cell response.

Time conflict with NEJM web update noted

Deep Dive talk by Ira B. Schwartz

Adaptive human behavior to control epidemics Ira B. Schwartz, US Naval Research Laboratory. Please click here for the slides File:Ebola AN deep dive.pdf


Discussion Notes

  • Emma McBryde: Hepatitis C network dynamics analysis shows that the most connected people can be found by following an edge.
  • Likely to be connected to people with high degree distribution so the infection quickly goes to a hub.
  • Hep C has been shown to spread among friends.
  • Find high degree nodes and use ring vaccination strategy.
  • Alex: Social distancing affects on Ebola (being afraid of your friend).
  • Ira: Leah Shaw and he looking at social distancing, but it's hard to get any kind of data.
  • Study on manipulation (put wash basin outside of men's room - people can see if you wash your hands or not). Use peer pressure to modify behavior.
  • Some behaviors early in the epidemic were counterproductive
  • Leah: Although there is a lack of data, modeling in her group shows that, if your social distancing increases as epidemic ramps up, and then goes back,

you can trigger oscillations.

  • James M.: Absolutely true. Shown for Influenza that social distancing can cause oscillatory dynamics (Australia, 2009 swine flu, other examples, Stephen Reilly paper
  • James will put references on the wiki
  • Emma: Seen in SARS but hard to resolve when simultaneous government intervention and decision making
  • Nic: Question on on clustering emerging in Ira's model: Does it break the network? At what scale?
  • Rewiring - can be reduction in efficacy if nearby people are also infectious (probably true)
  • Alex: Cell phone data sets hard to get. Suggestion to use 4SQ
  • Ira: In the first paper (Barabasi group), cell phone data was not quite anonymous
  • Want to get distribution function that describes peoples movements (??network topology??)
  • Alex: Nokia mobility data challenge data set is public. Will send link
  • Emma: global air travel. Group in Melbourne is quite interested. Would like to fill in regions for Australia. Offer to help refresh the data
  • Kun: several teams are deploying vaccines. Different vaccination strategies could me modeled and it might be worth discussing over.
  • Ira: Stratification of population - age dependence.
Items from Participants

Next Week Simone will moderate.

In two weeks Emma will moderate.

October 15, 2014 Call

Phone call will begin at 2pm ET (11AM PDT) to accommodate participants from Australia

Agenda

for October 15

Moderator: Alexander J. Jones, Operon Labs

  1. Welcome. Introducing
    1. Dr. Emma McBryde, Head of Mathematical Modeling, Burnet Institute, Univ of Melbourne, Victorian Infections Disease Service
    2. Prof. Jodie McVernon, Modelling and Simulation Group, Centre for Epidemiology and Biostatistics and Vaccine and Immunisation Research, Murdoch Children's Research Institute and Melbourne School of Population and Global Health
    3. Prof. James Mccaw, Modelling and Simulation Group, Centre for Epidemiology and Biostatistics and Vaccine and Immunisation Research, Murdoch Children's Research Institute and Melbourne School of Population and Global Health
  2. News
    1. Added link to stem-ebola summary on the home page
    2. Added Summary of Pub-Med news Items to our Ebola Reference Data page.
    3. Please copy (quantitative) new updates to the Ebola Reference Data. This way we can track the dates of key events (ie if we want to tally imported and secondary cases outside of W. Africa over time.
  3. Questions on expanding the community: Pro Med and other mechanisms (Alex, Jamie)
  4. Caitlin Update on VT hack-a-thon
  5. 20 minute deep dive topic: Ebola Deep-Dive Topic: Mutation and Fitness Landscape
    1. Ebola 2014 Mutation Rate: Comparison to previous Ebola outbreaks & Other Viruses
    2. Potential Impact of Ebola Mutations (tissue tropism, fitness landscape)
    3. Superinfection: Mathematical Properties / Evolutionary Dynamics
    4. Ebola Virulence vs Infectivity: Confounding Variables
    5. Recombination: Evidence for Horizontal Gene Transfer in Ebola
  6. Next week's agenda
    1. Ira B. Schwartz, NRL will moderate next week. Who would like to moderate in two weeks?
    2. Please send short agenda items to Judy by Monday
    3. Please suggest other themes and guests for presentation/discussion
    4. Next week's deep dive topic: Kun Hu & Simone Bianco model news on recent sensitivity analysis, SEIR++ Parameters
  7. Items from participants
    1. Question from NIHR UK

Minutes

Attendees
  1. Alexander J. Jones, Operon Labs, Moderator
  2. Jodie McVernon, Murdoch Children's Research Institute and Melbourne School of Population and Global Health
  3. James Kaufman, IBM Research
  4. Kun Hu, IBM Research
  5. Melissa Cefkin, IBM Research
  6. Judy Douglas, IBM Research
  7. Roslyn Hickson, IBM Research Australia
  8. Leah Shaw, William and Mary
  9. Stefan Edlund, IBM Research
  10. James Mccaw, Murdoch Children's Research Institute and Melbourne School of Population and Global Health
  11. Ira B. Schwartz, US Naval Research Laboratory
  12. Luis Mier, US Naval Research Laboratory
  13. Caitlin Rivers, Virginia Tech
  14. Raul Andino, UCSF
  15. Martin Meltzer, CDC Modeling Unit, Ebola Task Force
  16. Manoj Gambhir, CDC Modeling Unit, Ebola Task Force
  17. Thomas Gift, CDC Modeling Unit, Ebola Task Force
  18. Stuart Nichols, CDC Modeling Unit, Ebola Task Force
  19. Simone Bianco, IBM Research
Discussion

Question from NIHR in the U.K.. At what rate will (asymptomatic) individuals infected with Ebola pass undetected through airport screening at arrival airport if that screening involves only taking temperature?

IBM Research analysis: If we assume the passengers do not know they are infected, and if exponential growth continues, we estimate 80% will go undetected.
CDC Modeling Unit analysis: Based on the CDC model, if the passenger boards the plane in the asymptomatic state, 
about 90% will pass through the arrival airport undetected. At best 20% would be detected.

Caitlin Rivers gave a short talk with slides describing the recent File:VirginiaTechHackathonOct15.pdf held on Oct 15th.

Deep Dive talk by Alexander J. Jones

Oct 15th Deep Dive Discussion Slides up on the Operon site: http://www.operonlabs.com/?q=node/18

File:Deep Dive Oct 15 Operon Labs v1.pdf <--- * Download PDF of Operon 'Deep Dive' Slides

Discussion Notes

  • Discussed two definitions: Virulence vs infectivity
    • Virulence - mortality, morbidity
    • Infectivity - basic reproduction number. Inherent ability to spread
  • Impact of mutations so far: RNA virus - error prone polymerase. Churns out SNPs as well as insertions and deletions
  • Frame shift mutation might lead to unfit offspring that will die. Some may have better some worse fitness
  • Current outbreak, most common ancestor is 2007/2008 Congo outbreak
    • Absolute parent E. Zaiher is the 1976 concensus strain
    • Current virus 97% similar to concensus strain
    • ~400-500 mutations/substitutions = 3% difference
  • Fig 2b 3 clades small guinea clade. 3-4 subtypes. Feb-March is different from May/June. May be functionally the same but it is changing
  • Fig 3 shows 7 transcribed genes
  • 4 subclades of virus can be identified in different regions.
  • Don't know the impact on fitness
  • Virus mutation rate is accelerating
    • Rate is twice the mutation rate before this outbreak
    • This agrees complete with predictions by Bianco and Andino
  • Andino: The mutation rate is not uniform along the viral sequence, but depends on the type of mutation and position in the genome; Also, standard NGS may not be accurate enough to capture all the mutations; Finally, synonymous mutations may be important just as well as non-synonymous mutations, as they may have non-zero fitness effects and may contribute to the complex genetic landscape of the virus.
Items from Participants

Change of plans for next week's call. Ira Schwartz will moderate next week and give the deep dive

Simone Bianco will moderate in two weeks and give the Kun Hu/S. Bianco deep dive that week

So by convention going forward the Deep Dive speaker will be their own moderator (keeping their time to 20 minutes)

October 8, 2014 Call

Agenda

for October 8

  1. Welcome
  2. Vote on time change for call
  3. News
  4. New Eclipse tools
    1. Ebola community mailing list ( please sign up )
    2. Data page on wiki
    3. Literature references page
  5. 20 minute deep dive topic: Caitlin on Contact Tracing (lots of chatter from various sectors this past week)
  6. Next week's agenda
    1. Who would like to moderate?
    2. Please send short agenda items to Judy by Monday
    3. Please suggest next week's themes for presentation/discussion
    4. Next week's deep dive topic: Alex on SEIR Parameters (average or median regional values? values from a single paper? how to select for simulations?)
  7. Items from participants

Minutes

Attendees
  1. Caitlin Rivers, Virginia Tech Moderator
  2. L. Shaw, William and Mary
  3. Simone Bianco, IBM Research
  4. Kun Hu, IBM Research
  5. James Kaufman, IBM Research
  6. Judy Douglas, IBM Research
  7. Stefan Edlund, IBM Research
  8. Alexander J. Jones, Operon Labs
  9. Ira B. Schwartz, US Naval Research Laboratory
  10. Melissa Cefkin, IBM Research
  11. Mehmet Gunes, University of Nevada, Reno
  12. Pat Selinger, IBM Research
Discussion

Motion to hold the call one hour later for Australian Participants.

Motion passes without objection

Jamie: reviewed new community tools

Caitlin: Deep dive on contact tracing one of most basic public health interventions (interview patients to identify contacts) Contacts followed through incubation period In W Africa there are >20,000 active contact right now. Not going very well. G, SL public projects on following contacts they miss hundreds every day

Q from Simone: Once identifies as contact are they asked to quarantine themselves A no they are not isolated they go about their normal days until symptomatic

Q Alex: What is the maximum contact tracing can reduce an outbreak by?? A Varies by disease. If infectious during incubation it's not effective but with Ebola it is infective

Q is 50% reasonable A if worked perfectly it would be 100% effective. In practice it's 50-75% effective

Q can we use the contact tracing effectiveness data do detect secondary cases (ie from asymptomatic if there are any) A Ira: It's difficult due to uncertainty in the incubation period - was the secondary case asymptomatic or not.

Q Ira Do we know how tight communities are? DO they try to isolate communities from General population A Some natural isolation

Jamie: Firestone example

NPR
USA Today

Caitlin Two primary ways it can go wrong

  • contacts not seen (true now)
  • contacts lost to follow up (ie avoiding the tracing teams)

Montserrado county in Liberia has >200 lost to follow up

This is a major problem for control Call to modelers to think about this as a network problem or resource allocation problem

How can we be more efficient - place the monitors and bring the contacts to the modelers? Melissa: The network of people being traced. If we knew who are their family members (is that the network)? Caitlin: Could track them as well the contact teams should have that info

Ira: Watching videos. 1 contact tracing team for what seemed like 1/4 of the country. Has the situation improved? Caitlin: Not improved. LIberia does not have enough vehicles. No organization in how town is laid out (address associated with people not places)

Ira: Is there a model that would work in west africa that is not being tried? Local teams vs top down approach?

Jamie: Could we airdrop thermometers and send a text if you have a fever. IBM Kenya lab has cell phone reporting system... ie contact trace everyone.

Caitlin has DOD contacts asking for this. Jamie will connect to Kenya lab contacts

Done

Simone: Met with Raul Andino about the probability Ebola will become airborne. Prob is zero. Will it evolve so asymptomatic individuals shed the disease he said this is more likely. Any RNA based virus can evolve to have higher viral load without showing symptoms. We could implement Ira and Carlos' ideas to ask how would epidemic change if we get asymptomatic transmission. Alex: Highly probably but not enough cases yet (3000 people is not enough. with millions of people we might see case fatality rate go down but transmission could go up. There is a great book called Evolutionary dynamics (how virus explore). But depends on very large number of cases. Fatality might go down but not down that far)

Next Weeks Agenda Alex will moderate next week. Topic will be virology. Caitlin will also brief us on the hack-a-thon

Ira will moderate week after next will think about deep dive topic (and we can ask melissa)

Items from Participants

Items form Participants Kun would like to know about the hackathon at Virginia Tech Caitlin Today is the first day. Next three days are all out on it. Check back early next week.

Caitlin will invite people from DOD to this call. Ira: there are tri-service people that might be interested in joining (they are focused on pandemic modeling). Ira/Simone will exchange email viral evolution.

October 1, 2014 Call

Agenda

  1. Introductions
  2. Timing for Community Calls
  3. Purpose
    1. Not to push one model
    2. Not to advocate one tool
    3. Support Ebola response efforts
  4. Eclipse Community Tools
    1. This Call
    2. Newsgroup
    3. Mailing list instructions
  5. Overview of Ebola Model and four Ebola Scenarios uploaded to Eclipse
    1. Admin 0 three country model for West Africa
    2. Admin 2 three county models for West Africa
    3. All Africa Model
    4. The Global Model
    5. How to easily change from deterministic to stochastic
    6. Running STEM Headless on server
  6. Discussion on Literature models - please add references to this page
  7. Discussion on model parameters (latest wisdom, sensitivity analysis)
    1. Should we create a wiki page for ongoing discussion?
    2. Should we create a newsgroup topic for ongoing discussion?
  8. Next week's agenda
    1. Who would like to moderate ? We can rotate.
    2. Please send short agenda items to Judy by Monday
    3. Please suggest longer themes for presentation/discussion
  9. Items from participants

To receive agenda updates form our mailing list please:

Get an Eclipse ID: [4]
Subscribe to the mailing list [5]
See information on the STEM Community Join the STEM Community

Model documentation will be available on the wiki page Ebola Models

Minutes

Attendees
  1. James Kaufman, IBM Research
  2. Kun Hu, IBM Research
  3. Simone Bianco, IBM Research
  4. Judy Douglas, IBM Research
  5. Stefan Edlund, IBM Research
  6. Caitlin Rivers, Virginia Tech
  7. Sherry Towers, Arizona State University
  8. Bob Pinner, CDC
  9. Mehmet Gunes, University of Nevada, Reno
  10. Ira B. Schwartz, US Naval Research Laboratory
  11. Christian Althaus, ISPM, University of Bern
  12. Pat Selinger, IBM Research
  13. Vincent Ruslan, Operon Labs
  14. Carlos Castillo-Chavez, Arizona State University
  15. Melissa Cefkin, IBM Research
  16. Bryan Lewis, Virginia Tech
Discussion

Christian:

  • Science paper did not look at how mutations have changed properties of the virus
  • Population structure and control measures are quite different from countries
  • Parameters similar to previous outbreaks

Carlos:

  • This is a much bigger outbreak

Sherry:

  • The current Ebola outbreak seems to have relative low fatality rate compare to 90% in the record
  • Is asymptomatic transmission playing a role?

Bryan:

  • Is case mortality lower?

Sherry:

  • It seems to be lower.

Caitlin:

  • Up to 80% case fatality
  • Infectious period seems to be twice times than the previous outbreak.

Vincent:

  • What is the role of asymptomatic transmission. some numbers suggest something is different.

Jamie:

  • What is R0 for community, hospital, vs funeral transmission?

Sherry:

  • Suggested the transmission at funeral is 2-5 times higher.
  • Will provide some papers discussing different R0

Christian:

  • Really difficult to quantify different elements of transmission - restricted to total incidence data

Simone:

  • Conflicting data on under reported cases.

Sherry:

  • Who is collecting data?

Caitlin:

  • MOH of respective countries

Bryan Lewis:

  • Telecon with Neil Ferguson. Analysis of case listings.
  • The current endeavor is to explore these questions.
  • The data is partial

Christian:

  • STD transmission is probably minor

Everyone:

  • We need to get all the literature references in one place
Items from Participants

Caitlin:

  • Suggests we create a wiki page on Data
  • Ok to link to Caitlin's git hub and blog
Done: see new pages and please feel free to add content
Literature Ebola References 
Data Ebola Reference Data 

Sherry:

  • As a statistician, the work is data driven
  • We need better data to inform our models

Vincent:

  • Also concerned about asymptomatic transmission

Ira:

  • Interested in how people adapt their behavior in response to the epidemic outbreak
  • Also concerned about asymptomatic infectious classes. Can we back this out to predict asymptomatic?
  • Interested in agent-based model to study these type of questions

Christian:

  • Interest in opportunity for transmission in different small outbreak in Nigeria on how R0 (reproductive number) changes in a better urban setting where interventions were effective.
  • How does R0 depend on healthcare system of the country?

Pat:

  • Being in a community, how can we efficient and effective work together, what would help people respond more quickly?
  • Using a maillist does not address the issue when people want to share dataset.

Vincent:

  • Suggest to have a Ebola mailing
  • Parameters show this outbreak is going to be a 12-24 month long

Carlos:

  • Asymptomatic individuals: are they infectious or not? Very important in Influenza
  • Explore time dependent value of parameter
  • Critical to determine which of the additive factors contribute the most to R0 and Reff
  • Parameters change with different populations, different practices, different environment that may facilitate the transmission.
Follow up
  • Stefan Edlund created a new mail list stem-ebola@eclipse.org that will be active within 24 hours
  • Simone Bianco posted these minutes
  • James Kaufman created a new wiki page Ebola Reference Data

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