Huvepo Research Institute

We are committed to solving the problem that addresses the inequality and disparities that exist with the response to the COVID-19 pandemic. This is particularly the role of tech startups in influencing policy change and connection the general population with the different services needed to survive the pandemic. We are proposing a data research center that uses data analytics and statistical models to create the detailed analytical summary of the impact of COVID-19 for different demographics within the populations and the different regions with the country. This will create urgency within the different sectors involved in responding to the COVID-19 pandemic and back up the proposal with statistical algorithms that provides the need for focus to particular populations. Furthermore, if implemented effectively, it will cluster the different population demographics according to region helping us narrow their relation to different services like hospitals and government offices .

According to WHO, as of March 1 2021, there were 110 million confirmed cases with over 2 million people reported to having passed away due to the virus. In Zimbabwe for example where the total population is 14.8 million, there are approximately 107 new cases recorded daily with over 39 000 confirmed cases and 1632 confirmed deaths. To date, over 1 million vaccines have been administered in the country.

The impact of COVID-19 in Zimbabwe is relatively minuscule when compared to other parts of Southern Africa like South Africa that has 7 657 new cases  with 1.7 million confirmed cases and over 57 000 confirmed deaths. Unfortunately, administration of the vaccine has been slow with only 182 983 vaccinated in a country with a total population of over 58.5 million. 

We acknowledge that the statistic gives a blanket perspective, however, in terms of statistical rigorous significance, it is relatively a naïve summary of the impact of COVID-19. This leaves too much room for uninformed inferences of the affected communities in regards to urgency of vaccine administration or even basic care to high-risk areas. Therefore, the research center aims to effectively deliver a clear data analysis of the COVID-19 global pandemic through algorithms that carefully address the different classifications within the population both affected and in anticipation of a further outbreak.

This project was born in response to the COVID-19 global pandemic, which has magnified the disparities that currently exist in our societies, especially in regards to the preparedness of countries to respond in novel situations. That is the effective administration of measures for policy-making-related responses in affected communities. 

The core part of the project will be focused on the development of algorithms using population statistics. Using Algorithms will enable us to anticipate possible implications of disease outbreaks in communities, the different degrees of the vulnerability of the victims, and the creation of simplified narratives from the data collected from the population.  The research aims to focus on population in Sub-Saharan Africa with Zimbabwe being the first area of concentration.

We will use the Amazon Web Services of the data analysis particularly the Amazon Sage Maker, Amazon DynamoDB and the AWS deep learning containers. We went with the AWS as it is a cloud computing platforms that can easily accommodate the pilot stage of our research center and its flexibility in democratizing machine learning was a huge attraction to the platform. Furthermore, we plan on incorporating the GIS as our geospatial analysis software for detailed analysis and report.

The direct beneficiaries of the initiative are the different sectors (cooperate, government, and non-governmental organizations) that are involved in the intervention and response measure of COVID-19. This will also help the different communities at large with emphasis on trying to illuminate the different degrees of vulnerability and urgency within the demographic.

Currently, as a team, we are in the research mode of understanding infodemic statistics in relation to the different geographical contexts within Sub-Saharan Africa. We are also currently creating a model on the partners that we will be willing to engage with and the relevant procedures to get in contact with them are currently underway.

However, our first narrow population that we will be focusing on will be the Zimbabwe population data which is approximately 14.8 million people. We plan on using that data to effective cluster them into different region and then find the different patterns that exist with them in terms of their relation to the COVID-19 virus. Some of our assumed patterns might include but not limited to number of people affected per region, the number of people recovering per region, the different age groups per region, the different professions per region, the total number of the vaccinated per region and their different economic standing. 

What we aim to find out from the data is to identify the parts of the population statistic that has received little or no attention in terms of the response and advocate for them through sending such information to the people that might effective give them the services they need. We do understand that our capabilities to influence change and highlight the urgency is limited to the narrative of our data analytics. 

That is why we are passionate about using the best of services and resources like the amazon sage maker and the GIS software to make our backed up evidence as solid as possible. This is due to the fact that within the developing world, corruption has become so prevalent that when it comes to sensitive issues such as health care services they are the least are usually in the rural and peri rural areas. However, to eliminate the bias by automatically assuming which regions are most affected developing tools that do no leave anyone behind will help in creating the scale of vulnerability within communities where the most urgency is needed. 

Growing up in Zimbabwe form a working class, l have experienced first the short end of the stick as l lived through the 2008 economic crush within the country. Though, our drive is theoretical and far fetched representation of the voiceless, stories that are posted on YouTube about how for example the elderly are not getting enough food during the  lockdown within rural places in Zimbabwe is heart breaking. Not finding the basics like food highlight where they stand on the probability of being the first options for vaccines, mental health care services and just general knowledge of the the actual virus.

Engagement with the population will be from trying to connect with as many on ground patterns that are directly involved with the identified communities. We do hope as part of our future website and media coverage we will become not only a research center for innovation but a places of education that educate and removes stigma be it the virus and future diseases outbreak.

Our solution is the advocation instrument that highlight the under represented within the communities with strong analytical evidence to not only bring awareness of their condition but try connect with the national agencies with the capabilities to help them. We selected other as we go beyond the traditional data analysis but become the middle man of the people and the different services they need. With the partners and clients are literal fuel for data and the people we are advocating for the constant oil for our day to day operation as they are the ones to gain.

We are still a concept idea as the model of even the actual project has so much room for development but it sis a feasible idea that takes into consideration the magnitude of impact how data can influence the change that we need. Given the right credibility through partnership and effective mentorship, l think this might be the next big thing in the continent. 

From our proposed way of expansion where literary the young and bright passionate students from the respective country found through the UWC network replicate the model in their respective countries, is by far the best chance we have of effectively implementing this project as a whole and ensure rapid expansion which is needed urgently especially in relation to the COVID-19 pandemic.

We are taking possible ideas for a better big data manipulation to drive social change and entrepreneurship. 

Since this is a research center to be established, the first area of impact is within the research-related members in terms of their skills set that they would have gained from participation in the project. Their willingness to engage and create their own algorithms even beyond what our organization will offer will be resources that sets us apart from other solutions as the people are directly involved and part of the communities being helped.

Secondly, a more detailed analysis of infodemic statistics of firstly Zimbabwe and then potentially other Sub-Saharan countries in terms of clusters per location will be widely available both on our social media platforms and basic google search. This is different from just data analysis and publication as the narrative from the numbers is directly used in connection of the different service providers that will be willing to engage and benefit from the data analysis. 

Thirdly, we plan to get feedback from both the clients on our progress as an organization at the end of each project, with areas of improving our core highlight in the feedback loop. The sustainability of the project to be effectively carried out even in the months when all our team leaders are in schools will also be our milestone. External auditors will be introduced in terms of the financial part of the progress evaluation. Providing a secure data protection will be our emphasis as we interact with the different stakeholders and even in the event of expansion constant evaluation with suggestions from team members on how to improve this component will be crucial. 

The current number of people we are expecting to serve within the first months of implementation will be the 14.8 million people in Zimbabwe and effectively analyzing the patterns from the population statistics.One of the major focus is clustering people according to provinces which is an equivalence of states in US concept and then look at the population statistic per region and highlight the different patterns. This can be the different age groups affected by COVID-19, their recovery rate, the distances to the nearest health care centers and the number of people reported to have been vaccinated.

After effective implementation of our models, we plan on expanding to South Africa that is looking at population statistics of over 58.5 million people. Depending on how smoothly we get both access and partnership in the country of expansion we aim replicate the models we generated from Zimbabwe data sets and adjust them as per the demand. This will be our first year focus . 

Within the next five years, our expected number of impact is over 78 million population statistics data analyzed, that is looking at the countries within the Southern part of Africa. Though the direct impact of our statistical model is still unclear as it depends on the different partners and clients, we plan to branch beyond the health care sector to education and policymaking departments for maximized highlight on identified marginalized communities. 

We will measure the impact goals first by the quality of our analysis which inevitably depend on the quality of the data that we get. Therefore, methodical and careful partnership will be the first way to measure our progress. We want to partner with organizations that bring us into spaces of advocacy and inspire us to go back to our data and look for more patterns and evidence to attract more people on board of our vision.

We will also measure our impact goals by the quality not quantity of innovation from our team members and how many of our team members are able to branch out further into different communities for different services beyond the research center environment. We want to be a drive for reduced inequality, bringing in more representation with as many women willing to learn as our team members and at the same time maintain our carbon footprint through the solar field.

External auditors that go beyond the financial component, but also check the level of impact and alignment of our progress on a yearly basis will also be an effective measure of our impact goals. This is because we are a place of learning as much as we are a place of service so constant feedback and room for development will be equally important for not just evaluation but evolution of our model approach. 

Chimutsipa Sandra

she/her/hers

St. Olaf '23Psychology | International Relations | Management Studies

Student Government Association | ADC Coordinator

HT94 Student Organization Coordinator

Climate Reality Project Leader

chimut1@stolaf.edu

Cruz Martinez Sofia 

she/her/hers

Luther College `22 |Intenational Studies| Accounting|Economics

martso02@luther.edu

Thandeka Ruvimbo Chaka

she/her/hers

Luther College `23|Data Science| Mathematics (Applied Statistics and Calculus)|Computer Science

chakth01@luther.edu

Chimutsipa Sandra is the project strategist and coordinator. She has worked on two successful projects in that role "This is story initiative," in Zimbabwe and she recently awarded the Pestalozzi project recently launched as Tose Foundation in Zimbabwe. Additionally, she has had experience as a STAR Leadership advisor during her summer internships before St Olaf.

Cruz Martinez Sofia is the in-house financial advisor and accountant. She has helped friends in obtaining the Davis Peace Project initiative through her financial expertise. Furthermore, she has been a speaker at one of the UN conferences on the importance of peace and sustainable development. She also has experience in her successful art auction fundraising initiative with her friends where she raised money in support of people affected by flooding in her home country El Salvador.

Thandeka Ruvimbo Chaka is the project team leader and creative facilitator for the technical part of the project. She has experience on two successful projects on the "This is my story initiative" in Zimbabwe and her GoMakeADifferenceProject in Swaziland on teaching vulnerable girls how to make reusable pads using clothes and fabric. She will be working on her physics project as a data scientist and algorithm developer this coming summer using the IDL software. 

Our approach to building a diverse, equitable and inclusive leadership team is firstly addressing our biases as a female initiative research center. Our experience with international communities through the UWC movement will be greatly used to build a team that is in alignment with our mission and vision as a research institute. We plan on building a team that looks beyond educational background, economic status, race, gender and cultural differences but regard alignment with our purpose as a research institute as a key indicator of whether one joins our team or not.

We shall not be discriminatory or use language that gives one candidate a privileges' advantage over another. We plan on recruiting a team that is diverse and celebrates the differences within us and use that as a drive to even create more partnership and achievements.

We acknowledge the gap that exist between genders in terms of opportunities and we plan on at least recruiting 60 percent of our team to be people that identify as women and people that identify as part of the LGBTQ+ community more to create more than just representation but effective involvement so that when implementing change we are not just allies but have team members that relate on a personal level to the communities that we will be operating in. 

Above all a safe and encouraging environment will be fostered within our research center and hate speech or language within the spaces we exist with shall not be tolerated or even encourage be it in partnerships or everyday operations.

MIT Solve can help us achieve credibility as a research center that is nongovernmental among the different partners that we plan on reaching out to. In terms of accessing data and improving our business models, Global Challenge mentorship and possible partnership with Global Challenge members can be very helpful in contextualizing our solution and its implementation. Furthermore, it will provide us with an extra networking space for possible collaborations and areas of improvement.

As a group of undergraduate students with an idea burning inside us alignment with people with expertise in our future partnership environments will be more than useful for our success as a research center. Furthermore, we go beyond the traditional data analytics model with the social change at the basis of our innovation so exposure and partnership with people beyond our identified community as tech startup will broaden our understanding on social entrepreneurship wish solve will be a great platform for.

We want to expand our human capital to build a team that can work together to expand our work. Getting an effective team is important for us to ensure that we are fully achieving our goals. Another important aspect that we need help with is redefining our business model in efforts to make our vision clearer to understand. This enables us to pitch our ideas using a much better strategy for potential investors to invest in us and increase our source of funding. 

To also get as much of growth as possible we welcome as much support in different and possible areas within the research institute as possible.

We are looking to partner with organizations such as Higher Life Foundation (HLF) in Zimbabwe. This is an organization that has been doing a great job reaching out to communities addressing several issues such as education, health and more. Partnering with them allows us to reach a broader community and we also get direct guidance on how we can connect with different communities. HLF will also help us market out idea not only to direct beneficiaries but potential investors.

We plan on partnering also with any of of the MIT Faculty and initiatives that are in alignment with our goal as a research institute and service providing. We would appreciate effective feedback on how we can improve our proposed model, help with spreading our ideas to  people that might potential be willing to invest in us beyond the financial component and just highlight us as the next best initiative to be implemented within African context by young people affectionate about change.

We are an all female cofounded initiative that is advocating for social change and equity through data analytics. We plan to amplify and highlight the neglected members within the communities when responding to pandemics. Historically, women and girls have been denied space to express and effective implement their ideas by being denied access to the opportunities that might be available to them. Therefore we aim to be a catalyst for hyper woman visualization within the spaces there are not common represented and given voice starting with our research center.

We are a tech driven initiative that capitalizes on our data analytics and algorithm generation to inspire policy making and effective resource administration therefore, the prize will help further our potential to effectively implement this initiative to the maximum of our ability. By the nature of our initiative being a research center there is so much potential for different technological adaptation and creation within our space.

The solution goes beyond creating algorithms for the COVID-19 pandemic but given the market scope of our projected research location within the African context that still has on going tropical diseases to address, there is so much room for the adaptation of our models to influence change beyond the COVID-19 pandemic.

Moreover, our approach to scale through partnership makes us present with the health care service and that could be a great partnering benefit where the people that exist within the different service providers can also benefit from investing in the under represented and marginalized societies.