Right to Care and COVID-19: Strategic Information

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Background

As coronavirus (COVID-19) cases are increasing across Africa, national lockdowns and community screening programs are being commissioned as a means of flattening the curve quicker. A need exists for an enhanced surveillance approach, appropriate modeling, planning and responses using near to real time data to inform various interventions. This facilitates efficient data utilization and timely cost-effective interventions for various stakeholders that are involved and/or participating on the COVID-19 response mandate. RTC has taken a lead in various categories in response to COVID 19, this is based on RTCs prior experiences in similar emergencies, i.e. Ebola. The package presented in the current document present offerings in the following key areas: Enhanced Surveillance and Modelling; GIS mapping and Spatial Analytics; Practical Utilisation and Implementation of Analytic Outputs; and Hospital Bed Management. These offerings facilitate and strengthens Health Information Management across countries, provinces and districts with the primary objective of preventing and containing the COVID-19 using real-time data analytics to optimise patient care across Africa.

Objective

The objective of this document is to highlight the key support areas that RTC is supporting various countries predominately South Africa in responding to the global COVID-19 pandemic. The areas of support are based on existing models, analysis and tools that have been developed and implemented in South Africa. The support is outlined in four main areas: Enhanced Surveillance and Modelling; GIS Mapping and Spatial Analytics; Practical Utilisation and Implementation of Analytic Outputs; and Hospital Bed Management.

The presented package will facilitate the COVID key responses/interventions:

  • The rapid development of a social vulnerability index (SVI) for each province to identify areas that require close monitoring and rapid response should an active case be found: Prioritisation and targeted screening within communities
  • Predictive spatial modelling to anticipate potential outbreak areas and impact
  • Daily mapping of active cases disaggregated to suburb level for cluster identification and visualisation
  • Linking population and SVI data to the resource map of existing ward and ICU beds in public and private hospitals to predict infrastructure shortfalls
  • Determination of the optimal location for walk-in centres, drive-through testing sites and field hospitals based on the predicted need.

Summary of support areas

The support that RTCs Strategic Information provides is aimed at modelling the COVID-19 pandemic and expected resource needs for any country, which then feeds into effective planning and prioritisation, and finally using existing tools to practically utilise the results from analysis and implement effectively.

Key Support Area Brief Description
Surveillance and Modelling
Epidemiological Modelling

Projecting the COVID-19 disease burden in the country, and for each province. Projections include:

·       the cumulative number of total cases,

·       the active cases through time

·       number of hospital beds required,

·       number of ICU beds required and

·       projected deaths.

These projections are key for determining when and where there will be a shortfall of hospital and ICU beds, as well as modelling different COVID mitigation scenarios (e.g. lockdowns, domestic travel restrictions, social distancing measures, etc)

Health Economic Costing The team has worked on various costing aspects across the COVID-19 cascade, including testing costs and temporary facility costs.
Testing Capacity RTC will calculate the number of tests required and tests that the country has capacity for, based on the current resources (equipment) and the placement thereof. This can be split by province.
RTC GIS Support
Mapping & Spatial Analytics Support

The GIS team will map the following:

·       screening and case detection

·       active cases and their contacts;

·       socially vulnerable communities;

·       hotspots

This will enhance visibility of the areas most affected and that need urgent attention.

Optimal Location of Limited Resources

The GIS team will model the optimal locations for:

·       field hospitals based on current gaps in hospital beds;

·       isolation and quarantine centres for communities;

·       COVID19 specimen collection and logistics.

Rapid Data Collection & Visualisation Tools The RTC team can deploy tried and tested mobile applications for data collection that sync to near real time dashboards, all hosted on a secure access-controlled server.  These will be adapted from the ones deployed already.
Practical Utilisation and Implementation of Analytic Outputs
CHW & Field Team Management Tool to support field teams in mass screening projects. The project management tools include a ward level planning tool that assists with determining ward prioritization, human resources requirements and areas for targeting
Development of Mass Screening Modalities RTC can work with the MOH to determine which modality is best suited to which district and or province and support the immediate operationalisation of the same.
Hospital Bed Management
Hospital Bed Availability The RTC team has a tool that is used to track hospital bed availability and predict where and when hospitals will reach capacity.

* Support being rendered is already being and implemented in South Africa

** RTC support package is supported by RTC and its resource partner HE2RO

Details of support areas

Surveillance and modelling

Epidemiological Modelling

RTC is working with our resource partner HE2RO using a compartmental transmission model which was initially created to estimate the total and reported incidence of COVID-19 in the nine South African provinces as well as resource use and required budget to mitigate the COVID-19 epidemic. This model uses the NeherLab modelling infrastructure (https://covid19-scenarios.org/) utilizing the Susceptible-Exposed-Infectious-Recovered (SEIR) structure accounting for disease severity by age band (to determine rates of hospitalization and ICU admission). The model was re-configured and formatted in python and Javascript to include the population age structure down to the provincial level. The model is calibrated to the number of laboratory-confirmed infections, hospitalizations and deaths.

We plan to re-calibrate the model to other African countries to understand the expected spread, impact on the healthcare system, and impact of potential mitigation strategies. Given the unique of various African countries, this compartmental SEIR model will be applied to other African specific countries geospatial models to explore additional COVID-19 mitigation strategies unique to them. For example, instead of the ‘lockdown’ orders implemented in many countries, isolation orders could be implemented at a town/village level (such that a whole village or town could isolate together, should no COVID-19 be detected). Should undiagnosed HIV or active TB infection play a role in the transmission of COVID-19, we can include these parameters within the architecture of the model in order to further refine predictions and resource needs estimates.

The results of the epidemic modelling can then also be used to forecast the need for diagnostics, budget required, or further- to optimize mitigation strategies within a given financial or human resource constraint.

Example of COVID-19 Modelling Outputs

Health Economic Costing

The team has worked on various costing aspects across the COVID-19 cascade, including the cost of different diagnostics for COVID-19 (taking into account the test kits available and instruments available within country), additional hospital/ICU beds in existing structures or field hospitals, additional medical equipment such as oxygen and personal protective equipment (PPE) and possibly ventilators within the limits of human resource capacity.

Readiness assessments and testing capacity

The RTC teams has done facility readiness and testing capacity assessments for South Africa based on the different PCR instruments available in each province, and their possible capacity. Using different assumptions for working hours, staff availability and a reduction in HIV viral load testing, the team can produce estimates for the in-country capacity by instrument/reagent-type.

GIS Support

Mapping and Spatial Analytics Support

The GIS and Planning department will provide mapping and spatial analytics support, related to the entire COVID 19 cascade. This will include mapping and analyses related to: screening and case detection, mapping of active cases and their contacts; mapping of socially vulnerable communities; mapping hotspots. The maps below show examples of the potential mapping work that GIS can provide.

Map showing were socially vulnerable communities are located in a province

Optimal location of limited resources

The RTC GIS team will provide analyses related to ideal locations for: field hospitals and temporary sites; isolation and quarantine centres for communities; locational analyses related to COVID19 specimen collection and logistics; and analyses related to key gaps in the COVID 19 local level delivery response by area.

Maps used for optimal resource location

Maps used for optimal resource location

Rapid data collection and visualisation tools

The GIS analyses will also include spatio-temporal analyses of how COVID-19 is spreading and changing in-country. Furthermore, several GIS tools will be adapted and deployed to assist with:  data collection, provision of online/ real time GIS driven COVID-19 dashboards that display latest COVID-19 incidences by district. Figure 1 below shows an example of a data collection tool developed for COVID-19 teams.

Screenshots of mobile app developed to assist with screening

: Dashboard that summarises data captured by the mobile app in near real time

Practical utilisation and implementation of analytic outputs

CHW and Field Team Management

Planning for deployment of field teams to support mass screening for COVID-19 and door to door interventions, is a mammoth challenge. The GIS and Planning Unit has developed robust project management tools, which can be used by National, Provincial and District management officers to plan for efficient and rapid field work roll out.  The project management tools include a ward level planning tool that assists with determining ward prioritization, human resources requirements and areas for targeting.

Tool for Managing Field Teams

The ward level planning tool uses several planning variables like: desired house hold coverage; house hold size; time per household; travel time between households and several drop down menus (eg average travel time, total working hours in the field, total screening days) to calculate total screening days for a given ward.

The ward level planning tool is complimented with GIS tool that is run to determine the day to day team coverage (map a), with each team being provided with a map of the day to guide field implementation (map b).

Maps to be used by managers for planning and for field teams on the ground. Map a) Day by day operational map for field teams

Map b) Day 2 operational area, with imagery support

Development of mass screening modalities

RTC proposes the use of 5 mass screening modalities:

  • Self-reporting via an App or WhatsApp link
  • The management of high transmission areas such as shopping areas, health care facilities and taxi ranks
  • Self-reporting at health care facilities – hospital and clinic
  • The location of walk-in testing facilities
  • The management of hard-reach and/or rural communities

RTC can work with the MoH to determine which modality is best suited to which district and or province and support the operationalisation of the same.

Hospital bed management

Bed occupancy tool

The RTC team has experience in providing technical assistance with hospital bed management. Some of the key things to consider when making more beds available include:

  • Current beds available
  • Decanting beds to provide more beds, then
  • Activating Surge Capacity with additional space in the hospital complex, then
  • Adding temporary facilities on the site of the hospital, then
  • Establishing Field Hospital facilities, then
  • Activating mass care facilities

The RTC team has a Bed Statistics Dashboard that can be used to monitor Hospital Ward Capacity and inform resource allocation. When used effectively, the tool can be used to predict hospital bed shortfalls before they develop.