Developing infectious disease surveillance systems

The ongoing pandemic disease has taught us many lessons about change.

But are these lessons helpful to prevent subsequent outbreaks of the virus ?

Various publications have suggested that they can.  For example,  National Institute of Health, (USNIH) , John Hopkins Research Institute, Nature (R)  publication Communications offer support and information about how national and international systems could be molded to increase their readiness against local or global epidemics.

The largest volume of scientific publications shared research that reacted to early detection of the SARS-CoV-2 spike protein, as if recommending  to develop a solution via neutralizing monoclonal antibodies. 

Much of it assumed aerial transmission of the virus present based on animal infectivity experimentally. The assumption also led to the promotion of mouth and nose masks as effective solutions to prevent spread.  However these promotions by Nature and other publications were not necessarily accurate.

We offer a platform and tools to show that human infectivity and spread has nothing to do aerial exposure but rather strictly overwhelmed virus multiplication combined with targets that happen to be ingested by humans without public health warnings. 

The exposure in this way is part of the pathway that virus infection of humans has been so profound.   We provide the tools that can help to design policy and implement it to fight outbreaks within 100 days. 

Data and digital tools such as artificial intelligence and machine learning cannot represent more than 40% of the accurate forecast.  This is because the data that is used is already historical and less real by the time it is collected.  And so, we are more interested in the instantaneous progression of change in the real environment and ensuring computational models do not store data to predict the future outbreaks. 

To come up with an effective disease surveillance system and to fight against them, we need a green pro-ecological framework. Many research teams have devoted their attention to instances of events that describe interaction of the virus in the human host.  None, such as at the World Health Organization (WHO) have dedicated their research to pandemic-related virus ecology.  We are the leaders in that field and first to do so.

We are cutting-edge in a new forecasting field for technologists. 

To show digital data and computational models related to the epidemic and control, the system compiles a Collection system we update regularly as part of monitoring for client organizations and institutions. It is essential to acknowledge that variables for new diseases are not predictable with traditional or even the best available methods in epidemiology. A system that responds quickly to an epidemic or pandemic threat needs to be integrated with a variety of societal components and environmental ones as well. The resulting output is a collection that is expected to suggest possible remedial responses that are precise to the solution for saving lives and the quality of life that each human expects in the answerability of their government to them. The US NIH, Nature Communications and multi-disciplinary teams around the world have offered an Open Access model on behalf of regular updates for key issues in the pandemic form. It has taught us about the need for reorganization of healthcare and hospital access, the need to qualify acceptable and unacceptable parts of the economy relative to sustainability, and the preparedness of cities and infrastructures for biopathogenic warfare.  

For the future investigation, the products that we design are called ToolKits.  The system is launched for discussion online interactively. Experts from different fields are invited to speak and to share their experience and contribution to the fight against COVID-19 and to share their views on how a new disease can change lives. 

We too will bring more detailed information about mechanisms and dynamics of the strains that emerge, and describe that information to our audiences and clients. The new products give our client organizations the power to control liability against future pandemic outbreak risks. It includes the prediction of unknown and upcoming diseases. We work with new technology and consider the latest for computational purposes to do with genomic analyses, too But on the broad pandemic-free target, we are already extremely flexible enough to be integrated with hospital certification and environmental quality.  Truly, what we learn helps us learn how much room there is for more experts and decision-makers that enhance the performance of our pandemic-free (™) certification models. 

Wherever today’s confusion exists in decision-makers , guidance should be based on both modeling forecasts and real-time interaction insights on-site.  

We hope this brief document inspires you to join us, and to share your research on pandemic disease on our site.