Filipinos among AAPI groups affected most by COVID in California

FILIPINOS are among the top Asian American and Pacific Islander (AAPI) groups affected by COVID-19 in California, according to data presented by the state’s Department of Public Health.

The data released during a recent webinar was to inform the public on AAPI health data disaggregation and how the information can help facilitate better outcomes and support for the community.

The Filipino community was one AAPI group seen frequently throughout data presented within the webinar.

A significant part of the meeting was the presentation of collected disaggregated data that detailed leading causes of death among AAPI groups as well as statistics regarding COVID-19. Speaker Michael C. Samuel with the CDPH Strategic Development and External Relations Fusion Center spoke first on the data related to causes of death.

Samuel showed attendees a detailed chart that compared the rate of death for various AAPI groups based on specific causes that were ranked for each subgroup. According to the data presented by Samuel, COVID-19 was the leading cause of death for Filipinos in 2021, followed by ischemic heart disease, Alzheimer’s, stroke, and hypertensive heart disease.

This depicts how COVID-19 truly made an impact within the Filipino community, where it affected them the most out of all other AAPI groups in California. Data presented by Charsey Porse, who is with CDPH’s Center of Infectious Disease, detailed COVID’s impact even more.

According to the data that was provided, Filipinos have specifically shown a significant impact from COVID-19 based on the cases that had detailed information on race and ethnicity available.

“Among Asian patients (with known detailed race), the largest number of cases occurred within the Filipino, Indian, Chinese, and Vietnamese groups,” Charsey Porse, an epidemiologist with the CDPH, detailed.

Similar to the data provided by Samuel, Porse also revealed which groups had the highest death rates due to COVID. Once again, Filipinos were in the top of the list, alongside the Cambodian and Japanese communities. There was no data explaining why this was the case, however future data collected could lead to eventual conclusions and answers.

While this webinar addressed issues and disaggregated data for the AAPI community as a whole, its information is important to understanding how Filipinos fit within the AAPI community as well as what makes them different. The following sections detail the happenings of the webinar. The information acts as a crucial step towards transparency and understanding regarding health data within our community.

Data disaggregation

The issue of aggregated data takes a step towards being addressed through Assembly Bill No. 1726, written by Attorney General Rob Bonta when he was a member of the state Assembly.

With the passing of this bill, the CDPH became required (on or after July 2, 2022) to make available and collect demographic data that would include an expanded list of AAPI groups that were previously not included as subgroups. A full list of these groups can be found on CDPH’s website dedicated to the bill.

The type of data collected and how much progress has been made in the implementation of this bill was outlined in the webinar, which started with a welcome from Maral Farsi, deputy director of legislative and governmental affairs at CDPH. Attending and speaking were a variety of experts tasked with working together in and towards the implementation of AB 1726.

Karthick Ramakrishnan, chair of the California Commission on APIA (Asian and Pacific Islander American) Affairs introduced how there has so far been meaningful progress in implementation of the bill.

However, while there was progress, they also ran into challenges, specifically the pandemic. In light of this challenge, Ramakrishnan also made clear that the pandemic showed the “dire need” in collecting disaggregated data on AAPI communities.

“We know if we just collect data on ‘Asians’ we don’t have the kind of detailed understanding that we need to target the investments needed to make sure that our communities are being served adequately,” Ramakrishnan explained, hoping that this data will be used to aid in progress m ade for and within AAPI communities.

“Disaggregation doesn’t get at the heart of what this is about, which is data equity. Equity in the collection, analysis, and dissemination of data. But it’s also data to advance equity,” he added, noting the importance not only of the data but how it is used.

Rohan Radhakrishna, deputy director and chief equity officer with the CDPH’s Office of Health Equity, detailed how race and ethnicity data were collected, analyzed, and reported in five broad categories that were defined by the Federal Office of Management and Budgets since 1997, where AB 1726 is a step towards breaking down those categories for AAPI communities.

“Data disaggregation refers to the breaking down of collected data into smaller definable units to better illuminate underlying patterns and trends,” Radhakrishna noted. He went on to describe how each individual has a complex array of factors that affect their life and health.

Radhakrishna listed the following factors as immigration, socioeconomic status, nativity, language, and an individual’s experience as a minority with structural and intrapersonal racism. “These complexities are obscured when data is aggregated into broad categories,” he explained, adding that disaggregated data can therefore illuminate social and health disparities that were otherwise hidden by broader categories.

“Asians aren’t a monolith,” Radhakrishna expressed, where he elaborated how ‘Asian’ is often used as an umbrella term, categorizing groups of people into one. This can therefore “reinforce inaccurate and harmful notions of the model minority” as well as lead to disproportionate access to opportunities and resources.

Implementation 

Julie Nagasako, deputy director of CDPH’s Office of Policy and Planning, addressed key actions the CDPH has been taking to implement AB 1726.

“One of the critical steps that will improve our ability to share disaggregated data are updates to our vital records system, both for birth and death data,” Nagasako shared. She was transparent in expressing how as these implementations were made mid-year, in April and June, it would take a bit of time to have a complete year of data under the new protocols for collection detailed by AB 1726.

Nagasako emphasized that the collection and provision of this disaggregated data is not an effort made by one person let alone one department, rather a multitude of teams at CDPH are working on strengthening their coordination. They are aiming to build connections in an effort to better understand how to offer disaggregated data in a way that can help AAPI communities most.

Additionally, in order to ensure “data completeness” Nagasako expressed how the coordination extends to external partners as well. “AB 1726 has to do with how we manage and display the data that we generate,” she explained, highlighting that this data comes from a variety of sources, such as external surveys, federal data, and health systems to name a few.

Nagasako then spoke on another crucial part in the implementation process, where in order to make the disaggregated data available, it would be released bit by bit to the public. One of the resources she referenced, which was referenced by other speakers in the webinar, was the “Asian and Pacific Islander Data Disaggregation Brief.”

CDPH, according to Nagasako, will be incorporating disaggregated data wherever possible, such as an upcoming 2023 health assessment core module. She also noted how, based on feedback from the public, the CDPH’s website that houses the data brief will also include information about upcoming data releases, with links to where people can access them directly.

The data: Leading causes of death and COVID-19

As previously outlined, two speakers, Michael C. Samuel and Charsey Porse spoke on highlights from disaggregated data that has so far been collected and made available to the public. Both speakers were transparent with attendees throughout, even providing thorough analyses of various data and charts provided as an example.

“Different systems often collect race and ethnicity data with different categories,” Samuel declared before proceeding to show examples of aggregated population data in California. Referencing what Radhakrishna had detailed about how race and ethnicity data were collected, Samuel’s example of aggregated data only showed five broad categories, which included Asians and Pacific Islanders as separate entities.

“Looking at this disaggregated (or in detailed categories) is critical,” Samuel expressed. As a comparison, Samuel, then after, showed attendees charts of disaggregated data, which included a variety of AAPI groups. This highlighted how the aggregated data had so much missing.

The next set of data that Samuel presented was the chart comparing rates of death among AAPI groups. “COVID-19 is the top leading cause of death based on age adjusted rates,” Samuel described, noting that while there is this common thread amongst the data for different groups, there are still a variety of differences. For example, for the Chinese/Taiwanese group, “lung cancer is the fifth leading cause of death as it is for Vietnamese, but it doesn’t appear in the top five in the rest of the groups,” he said.

“In conclusion, great progress has been made in analyzing and sharing disaggregated race and ethnicity data. There are important differences observed between disaggregated groups,” Samuel concluded in his section, pointing out that this data should hence be interpreted with caution in order to get an accurate understanding.

Continuing from what Samuel had spoken about, Porse provided ample detail about data collected regarding COVID-19. “Relative case and death rates of COVID have varied across racial and ethnic groups throughout the pandemic,” Porse started, before providing statistics that showed that when 2020 ended, “28% of COVID-19 cases were missing race and ethnicity data.”

However, this data with CDPH has since improved.  “Cumulatively now, about 19.5% of our COVID-19 cases are still missing race and ethnicity information, which spans the entire pandemic period,” Porse emphasized the difference in numbers.

There is still of course more to be done as many of the cases that do include race and ethnicity data, specifically for AAPI communities, are still “missing data in detailed race ethnicity subgroups,” Porse explained. She then provided more numbers, where in 2020, around 5% of California COVID cases were reported among Asians and around 89% of those cases were missing detailed race information.

“Due to the amount of missing data, we cannot calculate rates for race groups due to statistical unreliability,” Porse continued, detailing how around 12% of California’s COVID-19 deaths in 2020 were among Asians and that 16% of those deaths were missing detailed race information. This highlighted that while data was being collected, they were not enough to completely tell the story due to the lack of disaggregation.

However, Porse reassured attendees that while there was “under-reporting of detailed race information,” which makes it “hard to measure disparities and draw conclusions across subgroups.” The CDPH intends to continue to improve on data collection as well as making it available to the public. (Amrylois Ferido/AJPress)