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Geointellect.Health

simulation modelling tool to predict the ANY virus

Россия, город Санкт-Петербург
Отрасль: Интернет и ИТ, Информация и СМИ, Медицина, Искусственный интеллект
Стадия проекта: Готов прототип или продукт

Дата последнего изменения: 23.04.2020
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Идея

Build a multi-agent model on your city with simulation of people interaction based on urban infrastructure, population, gathering places etc. https://rb.ru/opinion/koronavirus-v-msk/

Текущее состояние

It can be predicted with the help of COVID-19 spread simulation model, which was developed by Center for Spatial Research – IT company working with GIS-analytics in retail, healthcare industry and urbanistics – in collaboration with Research Institute of epidemiology and Microbiology of N. F. Gamalei.

Taking into consideration the simulation model of basic behavior of city dwellers and having thoroughly described the virus, it can be possible to simulate the distribution of any disease in space and time, which can be spread through airborne contact. That describes this project made by Center for Spatial Research developers who simulated millions of interactions of Moscow dwellers of different age groups based on multi-agent system.

“Having completed the project, we deployed the model as an independent module in the Russian software “Geointellect” within Moscow. We visualized the coronavirus spread as a timeline in a separate interface of Geointellect: from the zero-patient initial moment of disease till his recovery, – said Denis Strukov, CEO of Center for Spatial Research. – Right now, the quarantine is not considered in this simulation model, it shows the scenario without quarantine measures.”

According to model prediction, if one person get infected in Moscow at a specific address X, within next 30 days 5084 new cases of infection would occur. The red parts on the map describe the sources of origin and spread of the virus. Green parts are the recovered population from the disease.

https://rb.ru/opinion/koronavirus-v-msk/

Рынок

1) b2G - cities (50)
2) b2C Spin OFF services , f,e, mobile for prediction COVID19 in Addresses of the cities.

Проблема или Возможность

From time to time there were several epidemic outbreaks: some of them proceeded quietly, some of them – vastly and unexpectedly. As new viruses appear, epidemiologists face to new challenges and studying new cases. Most researchers visualize the official infected cases, some of them are trying to ‘model further’ the charts of distribution of disease spread and predict the number of cases around the cities and countries. But what happens if the first infected person appears in a particular city? How quickly will the disease spread, considering the characteristics of the city?

Решение (Продукт или Услуга)

To sum up, we have a unique chance to:

Build a multi-agent model on your city with simulation of people interaction based on urban infrastructure, population, gathering places, shops and shopping centers etc.
Enrich model with real geodata (from telecom mobile data if possible)
Make a prediction not only for 30 days but further (till 180 days from registration of the first case)
Provide the interface with prediction, visualizing the virus spread around your city and people interactions as well, including quarantine, social distancing and other government measures.
Consider the probability of mortality from virus.

+ it can be b2C mobile services for preficated any virus in addresess

Конкуренты

NYT:

https://www.nytimes.com/interactive/2020/03/22/world/coronavirus-spread.html

Washington Post:

https://www.washingtonpost.com/graphics/2020/health/corona-simulation-russian/

Преимущества или дифференциаторы

-visualization on the map (predict cases in the addreeses)
-predict in addresses near peoples in cities

Финансы

1) B2G
- average check = 1 000 000 USD / 1 cities 1st virus (second virus = 300 000 USD)
- total sales = 10 000 000 USD (per 1 year)
- total cities = 50 in diff countries

2) Spin OFF (b2C) - mobile service
- average check = 10 USD / 1 cities / 1 virus
- total sales = 30 000 000 USD (in 1st year) (3 000 000 cases Х 10 USD)
- total sales = 500 000 000 USD (for all differents virus)

Бизнес-модель

1) Enterprise license - b2g
2) SaaS services (web + mobile) b2c

Целевое назначение инвестиций

target = 50 cities in Europe and others
imitation of contacts in the cities
collect geodata (open + pay)
programmng web-interface
programming mobile
marketing b2g
marketing b2c

Предложение инвестору

5 000 000 USD
10 - 30% in a new companies Geointellect.Health (is not in Russia)

Команда или Руководство

Прохождение Инкубационных/Акселерационных программ

ФРИИ
GoTech
MTS Startup Hub

Победы в Конкурсах и другие награды

MTS Startup Hub

Фотографии

Фото 1 - simulation modelling tool to predict the ANY virus

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Идея
Текущее состояние
Рынок
Проблема или Возможность
Решение (Продукт или Услуга)
Конкуренты
Преимущества или дифференциаторы
Финансы
Инвестировано в прошлых раундах, $
Бизнес-модель
Целевое назначение инвестиций
Предложение инвестору
Команда или Руководство
Менторы-советчики
Лид-инвестор
Риски
Прохождение Инкубационных/Акселерационных программ
Победы в Конкурсах и другие награды
Изобретение/Патент
Фотографии
Видео о продукте