Disease whack-a-mole: COVID-19 vs. Vaccine Preventable Diseases
Sustainable Finance in R Final Project
Author
Joe Aumuller
Published
April 27, 2023
Executive summary
This analysis serves as an initial exploration of the effects of the COVID-19 pandemic on the global economy and efforts to combat vaccine preventable diseases (VPDs). Further, it proposes several items that require additional, in-depth exploration. COVID-19 played a major role in GDP growth disruption: it shrank available funds for health expenditures, ongoing VPD control efforts, and constricted flows to donor-dependent countries (citation needed). This contraction in available funds is compounded with an increase in vaccination efforts for COVID-19 which may have cannibalized resources and contributed to a decline seen in VPD immunization coverage. Finally, this analysis explores a case-study of measles which demonstrated a large decline in vaccination rates during the pandemic and poses a major public health threat.
COVID-19 shrank global GDP by 4.3% with the greatest effects seen in High and High-Middle Income countries and a halting of growth progress by Low- to Low-Middle Income Countries
While COVID-19 vaccine coverage increased, VPD vaccine coverage declined in many countries
Measles poses a large threat to public health both by its high rate of cases and declining vaccine coverage shown by 10 countries (50% of which are in Sub-Saharan Africa) with declining immunization rates below the 95% threshold for herd immunity
At a price of $4.47 USD/dose for the 2-dose MMR vaccine (UNICEF), the 128,000 recorded measles deaths (WHO) could have been averted in 2021 for <$1.2M USD
Vaccine Preventable Diseases (VPDs) & COVID-19
There are currently 25 diseases listed by the WHO as preventable by vaccines. These vaccines are essential in combatting dangerous infectious diseases that still plague communities world wide. Leading up to the beginning of the COVID-19 pandemic in 2019, vaccine preventable diseases were a major priority of international and domestic public health institutions. However, after the significant disruption of COVID-19 to the global and national economies, many budgets and resources dedicated to vaccine preventable diseases were re-purposed to containing and combatting COVID-19. Particularly in LMICs. While many vaccine prices are negotiated in forward-pricing contracts or government subsidies, there is still great potential for impact by sustainable finance investors both in the pharmaceutical industry for novel vaccine technologies as well as in the delivery of vaccines to vulnerable communities around the globe. To understand this impact it is important to better illustrate the effect of COVID-19’s disruption in the global economy, the changes to vaccine preventable disease transmission and vaccine coverage during this time, and the potential impact of increased vaccine coverage in particular cases like measles.
COVID-19 shakes world economy, health budgets
Beginning in 2019, the COVID-19 pandemic had a serious impact on the global economy. One that had rippling effects throughout different sectors, particularly public health. To date, there have been over 764 million cases of COVID-19 and almost 7 million deaths (Our World In Data - COVID Cumulative Data). The shock to economic growth globally and in developing settings was profound, shrinking world GDP by 4.3% in 2020. The economic impacts of the pandemic likely impeded ongoing efforts to control vaccine preventable diseases. The significant shock of COVID-19 its effects on global GDP out shadows the global financial collapse and any other events since 1990.
Code
#IMF GDP Growth Showing Magnitude of Change#Collapse by year to get global trendgdp_growth <- vax_explore |>ungroup() |>group_by(year) |>summarize(mean_growth_rate =mean(growth_rate, na.rm =TRUE)) |>ungroup()#Plot trendsgdp_growth |>ggplot(aes(x = year, y = mean_growth_rate)) +geom_line() +geom_label(data=gdp_growth, aes(x =2009, y =-.5, label="0.01%"), color="red", size=4 , angle=45, fontface="bold" ) +geom_label(data=gdp_growth, aes(x =2020, y =-5.5, label="- 4.73%"), color="red", size=4 , angle=45, fontface="bold" ) +annotate("rect", xmin =2008, xmax =2010, ymin =0, ymax =6, alpha = .2, fill ="red") +annotate("rect", xmin =2019, xmax =2022, ymin =-4.75, ymax =6, alpha = .2, fill ="red") +labs(x ="",y ="Global GDP Growth Rate (%)",title ="COVID Shocks GDP in 2020 largest in recent history",subtitle ="Shaded regions represent COVID-19 and Financial Collapse of 2008",caption ="Data Source: IMF | Data last updated 2023 | Visual by: Joe Aumuller") +theme_minimal()#Collapse by year to get global trendgdp_growth <- vax_explore |>ungroup() |>group_by(year, income_level) |>summarize(mean_growth_rate =mean(growth_rate, na.rm =TRUE)) |>ungroup()#Plot trendsgdp_growth |>filter(!is.na(income_level)) |>mutate(income_level =fct_reorder(income_level, mean_growth_rate)) |>ggplot(aes(x = year, y = mean_growth_rate, color = income_level)) +geom_line() +scale_color_npg(name ="World Bank Income Level") +labs(x ="",y ="Global GDP Growth Rate (%)",title ="GDP Shocks Reverberate Across Income Levels",subtitle ="Growth in LMICs suffer major setback",caption ="Data Source: IMF | Data last updated 2023 | Visual by: Joe Aumuller") +theme_minimal() +theme(legend.background =element_rect(fill ="ivory1", colour =1),legend.margin =margin(5, 5, 5, 5) )
Figure 1a: COVID-19 presents as the largest economic shock since 1990; far greater than the financial collapse in 2007-2009.
Figure 1b: Disruption of GDP growth to negative levels greatly affected High and High-Middle Income Nations. However, these countries already spend proportionately higher on health expenditure and likely had larger budgets to combat existing public health threats.
Figure 1: Economic disruption of COVID-19 pandemic.
Why does COVID-19 disruption matter for VPD control?
Leading up to the pandemic in 2019, cases of vaccine preventable diseases were declining against 1990 levels. This progress reflects vaccine distribution efforts as well as concentrated investment in research and development targeting these diseases. The relationship between COVID-19 and VPDs is complex in that:
COVID-19 largely spread throughout high-income nations with extensive travel and infrastructure networks; not necessarily the countries that have been fighting relatively high rates of vaccine preventable diseases
Linkages between healthcare budgets, expenditure, and investments were likely redirected towards COVID-19 but are harder to trace and differ by country/market
Vaccination coverage between COVID-19 and VPDs differ greatly by spatial distribution. After the start of COVID-19 many vaccination levels against these diseases began to decline, putting millions at risk.
Code
#|fig-align: center#|layout-ncol: 2#|column: page#Basic Map# Load the required librariescov_map <- vax_explore |>select(iso3c, country, cases, vpd, disease, coverage, year) |>filter(year ==2021& disease =="COVID19")# Get the map dataworld <-map_data("world") |>rename(country ="region") |>select(-c(subregion))#Join togethervax_world <- cov_map |>left_join(world, by =c("country")) |>filter(!is.na(coverage))# Create the choropleth map#----Cases----#ggplot(vax_world, aes(long, lat, group = group)) +borders("world", colour ="gray85", fill ="gray80") +coord_cartesian(ylim =c(-55, 120)) +geom_polygon(aes(fill = coverage ), color ="white") +scale_fill_viridis_c(option ="C") +labs(title ="Global COVID immunization coverage in first year of vaccine (2021)",subtitle ="Vaccination coverage (% Total Population) by country",caption ="Source: World Bank | Data last updated 2022 | Visual by: Joe Aumuller") +theme_void()
Figures 2: COVID-19 vaccine coverage up to 2021. Rising vaccine coverage by countries heavily concentrated in high income regions often least burdened by vaccine preventable diseases. Pandemic likely contributing to two-fold effect on VPD-vulnerable regions: shoring up of donor funds and shrinking domestic budgets to fight other diseases to reach COVID vaccination targets.
Investment & administration needed as VPD coverage declines
Amongst VPDs, measles poses a major threat with the volume of cases seen in recent years. Looking at the 10 least protected countries against measles in 2019, vaccine coverage continues to decline below the necessary 95% threshold for herd immunity. Vaccines are often purchased and distributed through forward-pricing contracts and agreements with multilateral institutions or NGOs like GAVI, UNICEF, and others. Because of this, there aren’t readily available marginal cost or free market pricing data available for many vaccines. However, UNICEF and the WHO provide contract price averages by year here detailing that measles vaccines range from > $1 USD/dose (10-dose measles-only vaccine) to $4.47/dose (2-dose Measles, Mumps, Rubella combined vaccine). With affordable options to combat the disease, COVID-19 is largely credited for delaying delivery and administration of the vaccine in 2021 (CDC). The decline in immunization coverage and pricing/dose data listed via UNICEF, clearly state a case for increased investments in vaccines. Streamlined supply chains, technology that improve dose-schedule and administratino, as well as increased stocks can all help improve coverage challenges.
Code
#Case Burdens by Disease vpd_trends <- vax_explore |>filter(vpd =="VPD",!is.na(cases), disease !="CRS", year >=2000) |>group_by(year, disease, disease_desc) |>summarize(case_trend =sum(cases)) |>ungroup() vpd_trends |>ggplot(aes(fill=disease, x=year, y=case_trend,color = disease_desc,group = disease)) +geom_line() +labs(title ="Measles Dominates Cases of Vaccine Preventable Diseases Worldwide",subtitle ="Suspected vaccination rate declines against highly infectious pathogen threaten control efforts",x ="",y ="VPD cases by disease per 1,000,000",color ="Disease",caption ="Source: WHO | Data Updated Through 2021 | Visual by: Joe Aumuller" ) +scale_y_continuous(labels = scales::comma) +theme_minimal() +theme(legend.background =element_rect(fill ="ivory1", colour =1),legend.margin =margin(5, 5, 5, 5) )
Figure 3: Despite universal declines leading up to 2019 pandemic, measles poses largest threat to global communities followed by mumps; both are preventable through combined measles, mumps, rubella vaccines (MMR).
Measles serves as a cautionary tale to public health preparedness in the advent of COVID-19. >61 million doses of measles containing vaccines were postponed/missed due to the pandemic (CDC, April 17, 2023). As vaccine hesitancy and supply chain issues rise across the glove, diseases like measles threaten to make a resurgence in cases and deaths. Looking across the 10 least immunized countries in 2021, 5 countries are represented by Sub-Saharan Africa while additional nations span multiple regions like the Pacific and Europe. COVID-19 known for its ability to infect others easily has an R0 (R-naught, a measure of contagiousness) of 1.4-2.8 (Achaiah et. al). This means that for every individual infected with COVID-19, on average, an additional 1.4-2.8 people will come into contact with the individual and become infected themselves. Measles has an R0 of 12-18 (Guerra et. al)…
Code
#Vaccination Coverage Rates in 10 Lowest Countries# Top 10 countries with lowest vaccination rates vax_low <- vax_explore |>filter(year ==2021, disease =="MEASLES") |>group_by(year, country, coverage) |>arrange(coverage) |>top_n(-10) |>ungroup() |>slice(1:10)# Facet wrap ggplot plot <- vax_explore |>filter(country %in% vax_low$country, disease =="MEASLES") |>group_by(year, country, cases, coverage) |>summarize(coverage =mean(coverage, na.rm =TRUE)) |>ungroup() plot |>ggplot(aes(x = year, y = cases, group =1, na.rm =TRUE, color = country)) +geom_point() +stat_smooth(method ="loess") +facet_wrap(~country, scales ="free_y") +scale_fill_npg() +labs(x ="", y ="Cases per 1,000,000", color ="Country",title ="Measles cases on decline but resurgence possible",subtitle ="Least vaccinated countries at risk after COVID-19 Pandemic",caption ="Source: WHO | Data Updated Through 2021 | Visual by: Joe Aumuller" ) +theme_bw() +theme(legend.position="none") plot |>ggplot(aes(x = year, y = coverage, group =1, color = country)) +geom_point() +stat_smooth(method ="loess") +geom_hline(yintercept =95, linetype ="dashed", color ="red") +annotate("text", x =1990, y =95, label ="") +geom_rect(data =subset( plot, country %in%c("Nigeria", "Papua New Guinea")), fill =NA, colour ="red", xmin =min(plot$year), xmax =max(plot$year),ymin =0, ymax =100) +facet_wrap(~country) +coord_cartesian(ylim =c(0, 100)) +labs(x ="", y ="% Population Vaccinated", color ="Country",title ="10 Least Immunized Countries in 2021 losing protection",subtitle ="95% Herd Immunity Target Falling Out of Reach",caption ="Source: WHO | Data Updated Through 2021 | Visual by: Joe Aumuller" ) +theme_bw() +theme(legend.position="none")
Figure 4a: Cases show dramatic decline since 2000, the results of various global efforts to eliminate VPDs in high-burdened country. However, many near-0 countries show the potential for resurgence in case-curves.
Figure 4b: Further evidence of potential resurgence in VPDs can be seen in nearly universal declines in immunization coverage. Most notable Nigeria and Papua New Guinea have pronounced declines during COVID-19. The red-dotted line represents the 95% vaccination coverage target for herd immunity.
Figure 4: Countries with 10 lowest rates of measles-containing vaccine coverage.
Conclusion
In the wake of a global pandemic, redoubling of financial investment in vaccine supply and distribution is essential to combatting VPDs and helping eliminate the infectious disease burden for many developing economies around the globe. Infectious diseases are responsible for high levels of morbidity and mortality world wide and greatly hinder the economic development of Low- to Low-Middle Income countries. This analysis results in the proposal of the following for further exploration and study:
How much did COVID-19 disrupt donor funding and national expenditure targeting vaccine preventable diseases?
What are the average costs to investors in R&D and delivery of needed vaccines to combat VPDs?
Given current case rates and deaths, what are the projected gaps in immunization and what are the “returns” on investments by policy makers and sustainable investors in the public health sector
