Efficient Allocation of Resources across Counties based on Population at Risk and Health Care Capacity is key in response to COVID-19 pandemic
Category: Health
By: Noah Wamalwa,
The constitutional right to the highest attainable standard of health is now confronted by the COVID-19 pandemic which is exerting adverse impact on the economy and indeed the health system. Towards this end, efficient allocation of resources to priority areas is vital in the fight against the scourge.
Towards this end, efficient distribution of the resources ought to be based on evidence of counties that face the relative high population risk from being infected relative to the health care system capability in responding to the pandemic.
While county governments are responsible for the provision of primary and intermediate medical services, it is evident that the risks of infection, the epidemiological burdens and investments in capacity differ, partly being explained by historical legacies and geographical factors.
IEA-Kenya together with Urban Institute, a think tank based in Washington DC, have developed Health Care Capacity Index and Population Risk Index. While the Population Risk Index aims to assess the relative risks that population in the 47 counties face with regards to the spread of the COVID-19, the Health Care Capacity Index assesses the relative capacity of the Counties to respond to these risks.
The assessment of capacity is based on the following 14 indicators: –
Recurrent Health expenditure indicator is included in order to assess the budget outlay in addressing short term expenditure needs such as wages for health personnel as well as operations and maintenance of health facilities and equipments; Health workers, Health facilities together with other facilities such as beds and cots are included in the Health Capacity Index to assess the capability of the health facilities to offer the health services or handle caseloads as and when it is required. Lastly, facilities on Access to Improved Water, Washing of Hands and Ownership of Mobile phones mainly assess counties on the level of preparedness towards preventing the spread and surveillance measures such as contact tracing and dissemination of public information.
On the other hand, population risk indicators are as follows: –
Here, the focus is mainly on the population at risk, that is, mainly the elderly population, urban population (where the population density is high, hence high rate of infection), Counties with high incidences of mortality and morbidity including HIV prevalence which as clinical evidence suggest they lead to weakened immunity in tackling the ailment. Nairobi and Mombasa are the main sources of the spread in Kenya, hence Counties that are closer to these cities face he highest risk of the infection. Finally, Game Parks and Museums being the main areas of interactions between the local population and foreign, high concentration of the visitors poses a challenge to high infections.
The score for each of the above individual indicator is a relative score on a scale of 0-100 where 100 is the highest score implying highest capacity/risk while 0 is the lowest score implying lowest capacity/risk.
Summary of the Health Care Capacity and Population Risk Index
Source: Author’s Compilation
As shown above, Capacity Index scores range from 57.3 to 8.6 while Risk Index scores ranges from 57.4 to 1.9, a reflection of high variation across counties in terms of populations that are at risk and the capacity of the health care system in responding to the risk. Embu, Nyeri, Nairobi and Mombasa rank the highest in the relative health care system capacity, alternatively, Mombasa, Nairobi, Kisumu and Nyeri top on the Risk Index, hence being counties with the highest population risk. As can be inferred from the results, the top counties are also among the highly urbanised and with high populations. In addition, Nairobi and Mombasa are Kenya’s major international port cities and have been the major sources of domestic infections. In view of this, containment measures ought to be enhanced in these areas to prevent the spread to counties that have less capacity.
On the other hand, West Pokot, Turkana, Mandera and Wajir trail in the Capacity Index – a reflection of a low health care capacity, partly explained by historical marginalisation and geographical factors. At the bottom on Risk Index, are Turkana, Garissa, Wajir and Mandera rank last largely explained by low population densities, low HIV prevalence and also the fact that geographically, they are farthest from the source of infection (Nairobi and Mombasa). In the short term, given the reported cases of 8 patients by 27th April 2020 in Mandera, traced from Nairobi. The containment measures, re-deployment of medical staff or sharing of resources, intertwined with safety net programmes are necessary to prevent the spill over effect in other low capacity neighbouring Counties while cushioning the population from abject poverty. Mandera, Wajir and Garissa also face the cross-border challenge cross border infections due to the porous border with Somalia, a country that has reported a surge in the COVID-19 infections (582 cases as of 27th April 2020), hence the need for multi-agency response to preventing the movement across borders.
In the short term, counties can utilize this data and in particular score on individual capacity score to prioritize resource allocation in areas of weakness based on population risk and in the medium to long term invest in the infrastructure such as medical labs and recruitment/incentives health personnel to address the low health care capacity.
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Efficient Allocation of Resources across Counties based on Population at Risk and Health Care Capacity is key in response to COVID-19 pandemic
| Post date: Wed, May 6, 2020 |
| Category: Health |
| By: Noah Wamalwa, |
The constitutional right to the highest attainable standard of health is now confronted by the COVID-19 pandemic which is exerting adverse impact on the economy and indeed the health system. Towards this end, efficient allocation of resources to priority areas is vital in the fight against the scourge.
Towards this end, efficient distribution of the resources ought to be based on evidence of counties that face the relative high population risk from being infected relative to the health care system capability in responding to the pandemic.
While county governments are responsible for the provision of primary and intermediate medical services, it is evident that the risks of infection, the epidemiological burdens and investments in capacity differ, partly being explained by historical legacies and geographical factors.
IEA-Kenya together with Urban Institute, a think tank based in Washington DC, have developed Health Care Capacity Index and Population Risk Index. While the Population Risk Index aims to assess the relative risks that population in the 47 counties face with regards to the spread of the COVID-19, the Health Care Capacity Index assesses the relative capacity of the Counties to respond to these risks.
The assessment of capacity is based on the following 14 indicators: –
Recurrent Health expenditure indicator is included in order to assess the budget outlay in addressing short term expenditure needs such as wages for health personnel as well as operations and maintenance of health facilities and equipments; Health workers, Health facilities together with other facilities such as beds and cots are included in the Health Capacity Index to assess the capability of the health facilities to offer the health services or handle caseloads as and when it is required. Lastly, facilities on Access to Improved Water, Washing of Hands and Ownership of Mobile phones mainly assess counties on the level of preparedness towards preventing the spread and surveillance measures such as contact tracing and dissemination of public information.
On the other hand, population risk indicators are as follows: –
Here, the focus is mainly on the population at risk, that is, mainly the elderly population, urban population (where the population density is high, hence high rate of infection), Counties with high incidences of mortality and morbidity including HIV prevalence which as clinical evidence suggest they lead to weakened immunity in tackling the ailment. Nairobi and Mombasa are the main sources of the spread in Kenya, hence Counties that are closer to these cities face he highest risk of the infection. Finally, Game Parks and Museums being the main areas of interactions between the local population and foreign, high concentration of the visitors poses a challenge to high infections.
The score for each of the above individual indicator is a relative score on a scale of 0-100 where 100 is the highest score implying highest capacity/risk while 0 is the lowest score implying lowest capacity/risk.
Summary of the Health Care Capacity and Population Risk Index
Source: Author’s Compilation
As shown above, Capacity Index scores range from 57.3 to 8.6 while Risk Index scores ranges from 57.4 to 1.9, a reflection of high variation across counties in terms of populations that are at risk and the capacity of the health care system in responding to the risk. Embu, Nyeri, Nairobi and Mombasa rank the highest in the relative health care system capacity, alternatively, Mombasa, Nairobi, Kisumu and Nyeri top on the Risk Index, hence being counties with the highest population risk. As can be inferred from the results, the top counties are also among the highly urbanised and with high populations. In addition, Nairobi and Mombasa are Kenya’s major international port cities and have been the major sources of domestic infections. In view of this, containment measures ought to be enhanced in these areas to prevent the spread to counties that have less capacity.
On the other hand, West Pokot, Turkana, Mandera and Wajir trail in the Capacity Index – a reflection of a low health care capacity, partly explained by historical marginalisation and geographical factors. At the bottom on Risk Index, are Turkana, Garissa, Wajir and Mandera rank last largely explained by low population densities, low HIV prevalence and also the fact that geographically, they are farthest from the source of infection (Nairobi and Mombasa). In the short term, given the reported cases of 8 patients by 27th April 2020 in Mandera, traced from Nairobi. The containment measures, re-deployment of medical staff or sharing of resources, intertwined with safety net programmes are necessary to prevent the spill over effect in other low capacity neighbouring Counties while cushioning the population from abject poverty. Mandera, Wajir and Garissa also face the cross-border challenge cross border infections due to the porous border with Somalia, a country that has reported a surge in the COVID-19 infections (582 cases as of 27th April 2020), hence the need for multi-agency response to preventing the movement across borders.
In the short term, counties can utilize this data and in particular score on individual capacity score to prioritize resource allocation in areas of weakness based on population risk and in the medium to long term invest in the infrastructure such as medical labs and recruitment/incentives health personnel to address the low health care capacity.
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