The impact of the COVID-19 pandemic on California farmworkers: Better local data collection and reporting will improve strategic response

1.Introduction

Relevant and reliable statistical information about the impact of COVID-19 on vulnerable populations is a crucial weapon for effective public health system response in fighting the pandemic in local communities, in states, nationally, and globally. Improved data collection, analysis, and dissemination of tabulations of statistical data to the public cannot be seen as a luxury because a key objective in the current battle against COVID-19 is to successfully modify public social behavior and to draw a broad spectrum of non-governmental organizations into partnerships that contribute effectively to a collective response.

I discuss the challenges confronted by local level public health agencies in configuring their public reporting to make the best possible contributions to the collective response to COVID-19 as it spreads through a vulnerable population in the San Joaquin Valley of California – immigrant farmworkers and their families. Most farmworkers in the region (84%) are long-term settled immigrants in low-income households, many of whom (57%) live in mixed-status households that include undocumented immigrants [1]. Despite federal and state government efforts to overcome the pervasive socioeconomic and sociopolitical barriers farmworkers face, I show they continue to be disproportionately impacted by the COVID-19 pandemic. The issues faced in this major agricultural production region, and others like it, urgently need to be addressed.

The United States’ public health system is highly decentralized – with states having the authority to decide and implement their own strategies for data collection and reporting. The states, in turn, often delegate responsibility for implementing COVID-19 surveillance to counties, or sub-state consortia of counties.11 While states and counties have the authority to determine their own surveillance strategy and actions, as well as detailed reporting requirements, CDC does require standardized reporting of the data submitted to it for national tabulation and disseminated via its National Center for Health Statistics and other routes such as its Mortality and Morbidity Weekly Report (MMWR). Because the United States’ public health system relies on local data gathering, analysis and reporting, county-level public health departments play a crucial role as a “feeder system” for national tabulations. Consequently, the integrity of higher-level state and federal statistical information rests on the functioning of their data-gathering, analysis, and reporting. I explore the underlying problems and progress to date (October 15, 2020) and go on to offer suggestions for improvement.

Although county public health departments have long been the primary source of data needed for state and national statistical epidemiological analysis of infectious disease, few were well-prepared to confront the challenges they face in generating and reporting statistical data on COVID-19. Federal mis-steps in making PCR/molecular tests widely available were the biggest initial problem. But subsequent delays in state funding and training for contact-tracers further compromised data quality as incidence of new cases increased rapidly statewide and in the San Joaquin Valley during the summer as the peak harvest season began.

This unfortunate situation stems in part from public response having been so seriously politicized – in the San Joaquin Valley, in California, in the United States and globally.

I demonstrate how improvements in current statistical analysis of the disparate impact of COVID-19 on a socio-economically disadvantaged population can improve detection of “hot spots” of COVID-19 prevalence and contribute to designing more effective interventions to reduce transmission. Lessons learned from the situation in this labor-intensive agricultural region are relevant globally – especially in countries that, like this less-developed region in an advanced economy, have extensive cultural diversity and suffer from the serious economic and sociopolitical inequalities that give rise to health disparities.

This case study of statistical reporting at the local level shows how improved local-level data collection, analysis, and reporting can better contribute to strategic and operational decision-making, first, by better illuminating health disparities affecting a vulnerable population such as farmworkers and, second, by improved monitoring of public health system response so as to identify priority areas for improvement.

I conclude that innovative local initiatives to improve access to COVID-19 testing can be improved by focusing less on quantity of testing and more on making testing encounters the fulcrum for more integrated service delivery including contact-tracing and support for isolation/quarantine. This type of service integration has a positive impact on both spread of COVID-19 and quality of data because it will decrease bias in the sample of individuals seeking and securing testing. Consequently, testing data will begin to more closely represent the overall population and more reliably track pandemic spread.22

At this point (October, 2020), after several crucial months of delays, nudged forward by newly-issued state regulations for reporting, some of the public health departments in the San Joaquin Valley, most notably in Fresno County, the largest county in the region, will be taking steps forward to improve data collection. Planned improvements include more widespread, free testing, increased availability of rapid-turnaround testing, and new partnerships with community-based organizations to develop multi-lingual, culturally-knowledgeable contact tracing teams to elicit better information on patterns of transmission. This shows that, despite financial constraints, progress in partnering with a broad network of community organizations is feasible when there is the political will and organizational commitment to improve

2.Conceptual landscape: Why does effective public dissemination of statistical information matter?

In the current 21st century era where widespread access to online information is paradoxically linked to equally widespread dissemination of fabricated information, it is not surprising to see that statistical analysis, reporting, and interpretation of the implications of pandemic-related information is a fiercely-contested battlefield. This is evidenced not only by public officials’vacillations and contradictory statements in messaging to the public but, also, by direct political interference at the national level in scientific reporting by CDC [2, 3, 4, 5].

Making reliable and actionable COVID-19 information available to the public is important for sound decision-making in a country that purports to be democratic. The hope is that by providing information that can be well understood to be relevant and directly applicable to a broad spectrum of audiences, public health officials might successfully create platforms for more thoughtful and systematic civic engagement. The expected result would be improvements in health equity and more effective response as larger and better-informed community-wide networks emerge to combat the pandemic.

The national-level conflict that has emerged in the United States about statistical reporting has been mirrored at the local level in the San Joaquin Valley with controversy about appropriate extent of dissemination of epidemiological information on outbreaks. The issue is manifest principally with respect to findings about case clusters in agricultural workplaces due to agriculture being an “essential industry” and major political force in the region [6].

Local public health systems have not adequately considered the potential utility of more systematic statistical reporting to the general public and diverse audiences (including farmworkers and other limited-English households) as a tool to improve health equity in the COVID-19 pandemic. National mainstream media such as the Washington Post, the New York Times, The Atlantic, and the Wall Street Journal have skillfully drawn on analyses by Johns Hopkins University Coronavirus Resource Center and worked diligently to configure published analyses so as to inform elite audiences but these information resources are not typically available to stakeholders such as immigrants and farmworkers or the community activists advocating on their behalf.

In summary, when one examines the landscape of information made available to either the main decision makers or the public, among the myriad challenges to be confronted in responding to the local current crisis of the COVID-19 pandemic at the local, regional, state, national, and global level is the need to re-examine traditional perspectives on

The notion that decisions about the kind of statistical data, analyses needed, and best ways to disseminate such information are “technical” ones best left solely to the “experts”, in this case public health staff and officials, is an unfortunate one because it results in defaulting to public sector “business as usual” where innovation is discouraged. This notion also rests on the now seriously-eroded assumption that epidemiological professionalism will be unaffected by the tumultuous sociopolitical environment of the government context in which public health professionals work. Statistical policy in the battle against COVID-19 cannot be effectively “insulated” from public involvement. But, actually, it will be more useful for approaches to statistical analysis and dissemination of reporting to be developed with the goal of informing a broader spectrum of data users and responding to their information with careful consideration and discussion about how statistical analysis can most effectively drive innovation to improve intervention strategy and widespread public engagement in the collective battle against COVID-19.

3.How, then, to move forward?

First, there is extreme urgency to reconsider conventional wisdom about the specific types of statistical information needed by public sector decision-makers at the federal, state, and local level and by the public at large. Second, there is an urgent need to improve the quality of data collection in the “feeder system” for state and national statistical reporting: county public health departments. My observations and analyses examine the following:

4.Tensions between analysis/reporting of information on the COVID-19 pandemic

The first epidemiological note about what later came to be known as COVID-19 was a report of a cluster of 27 cases of a pneumonia “of unknown aetiology” at the Wuhan Seafood Wholesale Market on December 31, 2019 [7]. On that day, two doctors, Li Wenliang and Xie Linka presciently notified colleagues via social media (WeChat) of “a possible SARS” outbreak at the market. Li was soon reprimanded by local police “for spreading rumors” but eventually widely acknowledged (after his death from COVID-19 in early February, 2020) as having played an extremely valuable role in sounding the first alert. In one of Li’s last interviews before his death, he said “A healthy society should not have only one kind of voice” [8]. Here, too, he showed a keen understanding of how authorities confront disease.

But subsequent experience in the U.S. and in other countries shows the pros and cons of dueling narratives about COVID-19 and SARS-CoV-2 transmission. In less than a year, there have been a multitude of varying interpretations of findings from statistical analysis of available data (e.g. about the necessity and/or utility of face-covering to mitigate COVID-19 transmission [9, 10], proportion of COVID-19 cases that are asymptomatic [11, 12] and what such a ratio implies with respect to response strategy. There has also been extensive controversy about statistical reporting, regarding who can be counted as ‘having died’from the disease (e.g. undetected deaths at home, classification of deaths of patients with co-morbidities).

Lessons learned to date about COVID-19 surveillance data and models based on reporting from local public health authorities and states are that, given the sensitivity of epidemiological analyses and modeling as a basis for decision-making in COVID-19 pandemic response strategy, there is utility to encouraging many statistical “voices” and analyses but that there is, also, a need to systematically report competing statistical analyses. Despite public impatience with technical caveats it is clear that backup documentation of definitions, analytic approaches, and uncertainties are crucial in order to avoid confusion and controversy.

5.Case study: Background of COVID-19 in the San Joaquin Valley of California and other farmworker areas of the U.S.

A region of California that has been particularly hard hit by COVID-19 is the San Joaquin Valley; and within that region a large population that has been particularly impacted by the pandemic are farmworkers and their families. The region has a multi-ethnic population of about 4.2 million, more than half of whom (52%) are Latinx, and almost one-third (38%) are immigrants (including, in addition to Latinx, among others, Hmong, Punjabi, and Filipinos). About 300,000 people in the region are agricultural workers and are another 350,000 are family members in farmworker households.

The COVID-19 pandemic appears to have reached the San Joaquin Valley slightly later than urban areas of the U.S. Pacific Seaboard. However, there is also some evidence that community spread had occurred earlier than had been initially believed; it is likely that sparse availability of PCR/molecular testing delayed detection of the first cases [13].

By mid-March, clusters of cases were reported in five of the eight counties in the region about at the point a statewide “shelter in place” order was issued by California Governor Gavin Newsom on March 18, 2020. By April 3, COVID-19 had been detected in all the counties of the region (Kern, Tulare, Kings, Fresno Madera, Merced, Stanislaus, San Joaquin). After an initial false peak in May, incidence of new cases finally peaked mid-summer in the region. As of October 5, 2020, the cumulative number of reported cases in the region was 137,043. Unfortunately, incidence of new cases then increased again.

6.Why Farmworkers? – Rationale for Special Focus within Public Health System Tracking of COVID-19

Over the past several months, a number of reports based on analyses of national, state, and local data show higher prevalence of COVID-19 among ethnic/racial minorities and worse outcomes. One of the most extensive recent reviews [14], for example, examined 79 “hotspot counties” (with > 100 new cases during the most recent 7-day period and increases or decreases) and found that the mean ratio of number of cases for each racial/ethnic minority population to cases in the overall population in each area ranged from 2.3 for Asians to 8.5 for Native Hawaiian/Pacific Islanders with the ratio for Latinx/Hispanics being 4.4. A Kaiser Family Foundation report from August, 2020 notes that it took longer for data to become available to assess disparities related to COVID-19 outcomes but that racial/ethnic minorities also experience higher age-adjusted rates of hospitalization (5 times that of Whites) and age-adjusted mortality [15].

Cumulative incidence of COVID-19 infection and hospitalization among Latinos is disproportionately high [16] and virtually all (97%) of California farmworkers are of Latino origin [17].44 But analysis of the COVID-19 patterns simply in relation to racial/ethnic disparities is not enough to assure equitable COVID-19 response.

Looking at national patterns, it is clear there are numerous factors in play that contribute directly to these observed racial/ethnic disparities [18, 19, 20, 21] and that “structural factors” and social determinants of health are the primary factors in spread. Considering how these multiple factors interact in the distinctive context of farmworker communities provides a reminder of the practical benefits if the public health system were to generate more actionable statistical analyses on COVID-19 within this particularly vulnerable sub-population of Latinos and use this information to shape ongoing strategy and intervention.

Mexican immigrant workers continue to be socio-economically disadvantaged, even after more than half a century of social, economic, and health programs targeted to them. Although many unauthorized farmworkers were provided legal status by the Immigration Reform and Control Act in 1986, they are aging and, inevitably, and now make up only one-third of the farm labor force, while the majority of farmworkers still lack legal status [22].

The California farm labor force, initially concentrated in fieldwork in orchards and production of row crops, now makes up most of the labor force in animal production and in packing and processing facilities – an important consideration in the context of COVID-19. Agricultural production in California is less seasonal than in other parts of the U.S. due to the diversity of crops in the state but there remain major peaks (August-September) and troughs (December-January) that affect farmworkers’ risk of COVID-19 exposure over the course of the year.

Another important consideration is that about 40% of California farmworkers are employed by farm labor contractors [22]. These labor contractors play an important role in the labor market by moving crews from one production site to another – a practice that contributes to social network mixing and may, therefore, be important in patterns of COVID-19 transmission.

Employment in an essential industry where social distancing is difficult and uneven and where crowded housing is prevalent makes the burden of COVID-19 even higher for farmworkers than for the overall Latino population. California took a step forward in doing by issuing a “health equity” metric for assessing counties’COVID-19 response in different communities within each county. However, this initial metric, while very useful, could be enhanced by including requirements for tracking and assessing adequacy of response to vulnerable populations such as farmworkers and, ideally, in sub-populations of farmworkers (e.g. indigenous-origin families, employees of farm labor contractors, women, middle-aged workers) [23].

Without expanded access to relevant and reliable statistical information, discussion among public officials, agricultural employers, farmworker advocates, and service system providers such as primary health care providers, hospitals, and the public at large, about the spread of COVID-19 will inevitably be inadequate. The need for this range of organizations and the public to have broader access to reliable and a broader range of statistical data stems from the fact that organizations’ decision-making as well as day-to-day public behavior rest to some extent on epidemiological evidence – even in the face of widespread efforts to pit science against “common sense” and undermine trust in scientists and “doctors”, i.e.  epidemiologists. Transmission of information within social networks is known to have a particularly strong impact on attitudes, aspirations, and ultimately, behavior. Consequently, there are both immediate and long-term practical benefits in the battle against COVID-19 to having a broader and more accurate menu of analyses available to diverse audiences because behavioral decisions (by organizational players, informal influencers in social networks, and indviduals) are made continuously based on key audiences’ ability to “digest” and consider the implications of statistical analyses and act on that information (e.g. awareness of nodes of transmission at super-spreader events, identification of geographic hot spots and relative risk of transmission in different physical contexts, prevalence of COVID-19 in different age cohorts).

Moreover, given the overall size of the farmworker population in the San Joaquin Valley region (about 300,000 farmworkers and 360,000 farmworker family members who make up about 15%–20% of the region’s overall population) it is obvious that farmworkers’ well-being in the face of COVID-19 must be of concern to the general public as well; there is inevitably diffusion of COVID-19 from “hot spots” to adjacent areas, through geographically widespread social networks and, among farmworkers and some other “essential” workers (e.g. truckers), mobility in moving from one place to another.

Effective response to COVID-19 spread needs to protect farmworkers and, just as importantly, their spouses, children, relatives, and others living in “joint dwellings” (the non-family members living “complex” households or compounds and sharing cooking facilities, bathrooms, and or sleeping space with a primary family). Due to the extent to which COVID-19 transmission takes place within crowded farmworker households [24], the farmworker family members who do not, themselves, work in the fields face risks quite similar to those farmworkers themselves confront.

Enhanced approaches to testing and contact-tracing in the San Joaquin Valley have potential for improved statistical reporting and more effective COVID-19 response in other farmworker areas of California. It can, therefore, benefit, all of the state’s 1.8 million farmworkers and family members. Enhanced approaches implemented in California can also be adapted to assure the well-being of more than 4.2 million farmworkers and family members across the United States.

7.What societal factors increase COVID-19 transmission in farmworker communities?

“Societal factors” is meant to denote demographic, socioeconomic, sociopolitical, cultural, and community contextual factors, including built environment, that determine the Rt of COVID-19 in a community – that is the real-time reproductive rate of the pandemic in a specific population living and working in a specific sociopolitical context [25].

There are several distinctive factors that make farmworkers even more vulnerable than other Latinos vis-à-vis COVID-19 – both in terms of risk of infection and outcomes among those who are infected. Major factors include: poverty, employment in an essential industry, immigration status, lack of health insurance, and prevalence of crowded housing. These factors are co-variant in the California immigrant population but there has not been, to my knowledge, any comprehensive multi-variate analysis of the overall correlation with risk of contracting COVID-19 or outcomes.

It must be recognized, also, that sociocultural factors such as literacy levels, most-utilized sources of health information, structuring of social networks, and modes of day-to-day interaction in community life have consequences for transmission.

Some of the principal factors which interact to make the population of farmworkers and their family members particularly vulnerable are.55

8.Discerning patterns of COVID-19 impact in the farmworker population

Generating insights about COVID-19 in the farmworker population by looking at farmworker communities is more useful than seeking to begin with improvements in enhancing data collection from individual cases. The reason is that collection of occupational data from individuals interviewed by contact-tracers is difficult and potentially misleading (especially for the most seasonal workers who may work in different jobs over the course of the year). At the same time, standard North American Industrial Classification (NAICS) taxonomy of industry sub-sectors and Standard Occupational Classification System (SOC) taxonomy of occupations make it difficult for data analysts processing information from case tracing of COVID-19 cases to reliably code responses so that subsequent tabulation by occupation is seriously flawed.66

Community-level analysis aligns quite well with the actual risk factors experienced by farmworkers, because COVID-19 transmission is a two-way street where an infection contracted in the workplace is often transmitted to the home and vice versa. Transmission does differ in various “domains” of daytoday life of sub-groups in diverse communities but the reality is that these analytic “compartments” are permeable and, inevitably, linked. In farmworker communities, in-household transmission is likely to be extremely high, and thus heightens the linkage among the various domains where transmission can occur.

It is, possible to systematically identify farmworker communities using American Community Survey (ACS) data on local employment [44] and, then, by moving to tabulate prevalence and incidence of COVID-19. COVID-19 is routinely reported by zip code and easily linked to the ACS-derived detail on community characteristics. In addition to being practical, this approach reflects the epidemiological reality that although occupation is a significant risk factor for COVID-19, as a result of two-way transmission between worksite infection and within-household infection, farmworkers’household members are directly affected by the occupational risk of household breadwinner(s).

These community-level correlates of COVID-19 impact are documented in Table 1 showing the disparate impact of COVID-19 on farmworker communities in Fresno County and in Table 2 showing the disparate impact on farmworker communities in the Coachella Valley region of Riverside County, and in Table 3 showing disparities in farmworker communities in the Salinas Valley of Monterey County.

8.1Fresno county farmworker towns

Fresno County is the second largest county in the United States in numbers of farmworkers [45] and, has a relatively large number of easily-identified separate farmworker communities within this geographically large area (15,570 km2). Moreover, the farmworker population in the county is demographically and socioeconomically very similar to that of the entire Pacific Coast area of the United States (California, Oregon, and Washington) where more than half of U.S. farmworkers live and work. Figure 1 shows the 8-county San Joaquin Valley region and Fresno County within the area.

Figure 1.

Counties of the San Joaquin Valley, California.

The tabulations in Table 1 draw on widely-available data and are designed to be easily replicable and provide actionable insights of the magnitude of the disproportionate burden experienced by farmworking individuals and families in these communities, and to guide strategic response to COVID-19 based on the patterns that emerge from such tabulations.

Table 2

Ratio of COVID-19 cases in Eastern Coachella Valley Farmworker towns to county and state September 11–16, 2020

Column ref #	1	2	3	4	5	6
Community	Population	Confirmed cases	Cases Per 100K	Community to county ratio	Community to state ratio	Testing per 100K
Oasis 68% FW HHsize = 2.9	3,020	313	10,364	4.9	5.8	42,400
Mecca 41% FW HHsize = 3.7	7,174	416	5,799	2.8	3.3	23,500
Thermal 18% FW HHsize = 2.9	1,359	161	11,847	6.7	6.7	N/A
North Shore 23% FW HHsize = 3.2	2,892	122	4,219	2.0	2.4	18,200
Small, predominantly FW communities	14,445	1,012	7,006	3.3	3.9	28,033
Coachella 20% FW, HHsize = 3.1	46,813	2,507	5,355	2.5	3.0	26,600
Indio 11% FW, HHsize = 3.1 [100j]	93,738	3,440	3,670	1.7	2.1	24,500
Urbanized communities w/ some farmworkers	140,551	5,947	4,231	2.0	2.4	25,550
Riverside Co. 1.5% FW HHsize = 3.3	2,517,830	52,909	2,101			16,400
State of CA 2.3% FW, HHsize = 3.0	39,780,000	707,896	1,779			33,312

* 2018 research by the author [100g] suggests there is a significant underrepresentation of the farmworker population in Mecca (in the range of 5%–8%) due to census omission of “low visibility/hidden” housing units[100i]. There are likely to be similar biases in census data for the other farmworker communities in the area. As a result of undercounting the farmworker population, household size in the farmworker communities is almost certainly larger than reported and proportion of farmworkers higher than reported in the American Community Survey data. Data on testing per 100K population for Riverside County is from 9/16/20 and for California from 9/11/20.

Table 2 (for the Eastern Coachella Valley) and Table 3 (for the Salinas Valley) show how the approach can be customized to examine local patterns of COVID-19 prevalence in other California areas with concentrations of farmworkers. Both are major areas of labor-intensive agricultural production.

Comparing columns 2 and 3, Table 1 shows that the farmworker communities in Fresno County are disproportionately impacted by COVID-19. Even though Fresno County is a Latino-majority county (54% Latino) and has a much higher cumulative incidence than the state as a whole (see ‘Comparison Areas’in the table), farmworkers and their families are still more adversely impacted than the Latino population overall.

9.What Next? – Improving local statistical reporting on the impact of COVID-19 on farmworkers

The State of California has attempted to address an important shortcoming of county-level reporting on COVID-19 impact – the problem of uneven levels of testing in some counties – by incentivizing county public health system efforts to increase testing rate. State approval of county plans for “opening up” their economy, moving up in tiers of increasingly relaxed social distancing regulations for businesses, is based on metrics showing that counties are conducting adequate COVID-19 testing based on a formula incorporating positivity rate among tests reported adjusted by adequacy of local tests/100K population as compared to overall testing in the state [47].

This policy provides a good example of commitment to strategic decision-making based on systematic analysis of easily-available statistical information. But further progress will be needed – both in developing metrics that encourage more granular analysis of transmission patterns and in improving representativeness of testing data collected and reported.

What next? More attention needs to be paid to farmworker communities – attention that contributes to informed decision making, program design, interaction with the people in the communities, and assessment of progress. As can be seen from the preceding analysis, it is possible to “zoom in” on these populations of interest, if it is considered necessary and useful to do so. Both a failure of political will and failures in reporting design and collection methodologies account for the current lack of focus.

Statistical reporting on COVID-19 among farmworkers and other high-risk populations needs to be seen in the context of the national reporting system and overall strategy of targeted response to counter pandemic spread – in high-risk groups and in geographic areas where surges are observed. Targeting strategy is now being addressed in national planning for a vaccination campaign but it will be important to remember that, for many months after a vaccine becomes available, non-pharmaceutical interventions will necessarily continue to be a major weapon in fight against the pandemic and that enhanced statistical reporting will be a key underpinning in making that mode of response effective.

The indicator I focus on here, cumulative incidence of confirmed cases, is an imperfect indicator of the full impact of COVID-19 in any community because such a high proportion of cases are asymptomatic and because current incidence of new cases better reflects the situation at discrete points in time. Nonetheless, it is likely that “hotspots” of COVID-19 spread identified on the basis of cumulative incidence will continue to be relevant to analysis because models’“nowcast” estimates of R𝑒𝑓𝑓 have limited geographic resolution and continue to fluctuate due to the noisiness of short-term detection (weekly incidence of new cases) in small areas (e.g. census tracts, communities, neighborhoods with a population of < 10,000).

10.County COVID-19 dashboards: Public access to information to shape community-level behavior and strategic response

Johns Hopkins University developed the first COVID-19 dashboard to provide online COVID-19 reporting to the public. It was first shared publicly on January 22, and subsequently reported February 19 in The Lancet [48]. This provided an initial, thoughtfully-configured, template for national reporting. The template was also made available to local public health departments and was soon adopted by many. COVID-19 dashboards came to be the primary approach to disseminating local information on the pandemic to the public and stakeholders. Although the traditional approach of holding periodic press conferences to disseminate summary information continued in parallel in some places, the dashboards appear to have been, from the beginning, the primary vehicle for sharing statistical information on the COVID-19 pandemic.

The importance of effectively communicating statistical information on COVID-19 to the public stems from two distinctive features of the SARS-CoV-2 virus. The first consideration is that, due to its “novelty” as a human pathogen and absence of pre-existing immunity, it is clear that, for an extended period of time, “non-pharmaceutical interventions” – messaging and government actions to influence social behavior – will be critical.

The second consideration is that the virus’ intrinsic reproductive factor (R0) is high enough that there can be exponential spread – “explosions” of COVID-19 out of “hotspots” and that Rt may, in some identifiable populations and identifiable sociocultural contexts and types of built environment, be much higher than others. Confronted with this challenge, detection of hotspots and public communication tailored to diverse situations needs to play a major role in strategic response to the disease. Detailed geographic depiction of patterns of spread is therefore necessarily part of the narrative to better inform people about their immediate situation in the communities where they live and work.

11.Principles for standardized reporting on key aspects of pandemic spread and system response

From the beginning, the counties’ COVID-19 dashboards reported several standard epidemiological indicators: cumulative incidence of confirmed cases, new cases in past week, in a 2-week look back period, hospitalizations, and deaths. However, by the end of April, 2020, despite President Trump’s announcement that social distancing initiatives could be relaxed “by Easter”, as the initial surge of COVID-19 peaked and first began to subside, a high-level framework of metrics for evidence-based strategic response to the pandemic was proposed as part of national discussion of evidence-based decisions about “opening up”, conditions for relaxing social distancing [49]. However, although the task force that developed the metrics was led by former Federal Drug Administration (FDA) Commissioner Scott Gottlieb, the proposed framework for evidence-based “opening up” became controversial and was never adopted.

Then, in July, 2020, a comprehensive and reflective assessment of national reporting required for optimal pandemic strategic response was published by Resolve To Save Lives, a prominent organization headed by former CDC Director Thomas Friedan [50]. This analysis was not specifically about local COVID-19 dashboards but had direct relevance since it put forward recommendations for overall metrics in analysis and reporting of epidemiological data. Major issues identified in the report included lack of uniformity in tabulations, the need for more granularity in reporting, and indicators for assessing public health system performance. The COVID-19 reporting constraints highlighted in the report are evident not only in examining inter-state variations but also in the intra-state statistical “feeder system” of county-level reporting in California and most other states.

12.Where we are at now – as of November 2020 – local public health system generation and dissemination of statistical information on COVID-19

Local-level statistical reporting, within the United States, and internationally, can contribute to or distract from efforts to work more strategically to reduce health disparities affecting vulnerable populations. In the current 21st century context, the abstract ideal of epidemiological professionalism in decisions about information dissemination needs to be nurtured with efforts to enhance appreciation of the ways in which effective communication can help or hinder civic engagement and public behavior.

Although the San Joaquin Valley region of California is a major “hot spot” for COVID-19, county COVID-19 dashboards do not yet provide the general public, local stakeholders, public officials, and organizations with adequate information to have the required impact on public attitudes, aspirations, and behavior – the factors which are actually the key determinants of transmission.

As we move into the winter 2020–2021 flu season, as “lockdown fatigue” increases, and the public grows wary of constant re-framing and revision of COVID-19 “facts” and issues – we really need to improve the use of statistical information as a tool for positively impacting public behavior – including sub-population such as farmworkers. It should be appreciated that sound and systematic statistical reporting can play an important role in improving currently uneven public compliance with measures to reduce transmission. The San Joaquin Valley public health departments have made gestures in that direction, but effectiveness of communication varies greatly from county to county.

In particular, published statistical tabulations should, as part of reporting on patterns of COVID-19 prevalence, incidence, and trends, be adequate to allow stakeholders and the public (especially particularly vulnerable groups such as nursing home residents, and different high-risk occupational groups such as farmworkers and frontline responders) better understand the distinctive infection risks they and their families face.

Statistical reporting, in addition to tracking the course of the pandemic, also needs to provide a basis for assessing the adequacy of public health system performance in confronting COVID-19. Transparency in reporting about the spread of COVID-19 is needed but, just as importantly, information is needed about steps taken by the public health system to confront the pandemic and how successful those efforts have been in order to assure accountability of the public health system.

In the San Joaquin Valley region where fiscal conservatism dampens local government commitment to making necessary investments in public health interventions to combat COVID-19 it is necessary to give special attention to provisions which make it possible to monitor and evaluate system performance in responding to it and, on that basis, advocate for necessary changes in strategy and/or implementation of response measures. The sociopolitical dynamics relating to official statistical reporting on COVID-19 in the San Joaquin Valley are akin to those that will need to be confronted internationally, especially in countries where public sector concerns about the economic consequences of social distancing mandates detract from attention to public health dimensions of the pandemic.

For example, in Fresno County, officials deferred allocating $29 million of federal CARES Act funding earmarked for emergency response to the COVID-19 pandemic in the hope that their lobbyists could make Congress change federal law to allow the definition of “COVID-19 emergency” to be expanded to include the negative fiscal impacts that state “shelter in place” regulations had on county government revenue from sales tax [51]. However, by late summer, as a result of external pressure, county local government approved promising partnerships between the public health department and community health centers to expand availability of free testing, complemented with efforts by trusted community-based organizations working in different ethnic communities to promote testing and support contact-tracing.

It is unfortunate, there was delay in taking these very practical steps, but, once implemented, they have the potential to increase the effectiveness of efforts to curb COVID-19 transmission and improve statistical reporting. There are, however, many uncertainties, about the extent to which they will significantly impact COVID-19 prevalence. If, as some models project and as October data suggest, incidence of COVID-19 ramps up faster than effective contact-tracing can be conducted and proactive isolation efforts are put in place, the impact of this promising model may be minimal.

Table 4 below summarizes the current status of local county COVID-19 dashboards in October, 2020–seven months after the dashboard were instituted. The indicators included in the table draw on Resolve to Save Lives’indicators needed for national response to the COVID-19 pandemic. They are somewhat scaled-down from the national recommendations to a level that would seem more appropriate for statistical reporting by local government entities.

The reporting and presentation of information on the county dashboards has improved greatly over the eight months since the pandemic first emerged in the region. For example, Fresno County’s COVID-19 dashboard that had early on reported cumulative incidence of cases/100K population now also includes a community-by-community indicator of testing adequacy (tests/100K population). Merced County’s COVID-19 dashboard, now includes a line graph of cumulative cases that usefully shows the changing slope of increase in cases in different communities.

Yet, at the same time, the divergence in local presentations as each county pursues its own reporting trajectory reflects different priorities about the information that deserves to be made public without any consistency in visualizing how public dissemination of statistical information might make the most practical contributions to strategic response. Despite the amount of data that is included on each dashboard, there is little evidence of careful consideration or inter-county coordination about what sorts of tabulations or presentations might best support sound decision-making by the diverse audiences who need it – e.g. public officials, partnering local organizations, different segments of the public, etc. Parents of school-age children, as well as the K-12 school system, might be interested in prevalence among children 5–18 years old. Agricultural employers might be interested in prevalence in the farm labor force. However, these “user-oriented” statistical analyses, even those that require only straightforward cross-tabulation, are not available.

13.Improving the utility of COVID-19 data reported by county public health departments

Improving public health system performance requires both improvements in reporting and in data quality. The summary review of current reporting available on counties’ COVID-19 dashboard in Table 4 provides a framework for considering what improvements in reporting might be needed to nurture more extensive and thoughtful public engagement. I discuss these improvements first and then go on to discuss ways to improve data quality.

14.Conclusions – The role of local statistical reporting and how it can and should help to stamp out COVID-19

The traditional view that epidemiological data, statistical analysis, and findings should simply be produced, framed, and disseminated to communicate with a relatively homogenous audience of professionals is untenable in the context of COVID-19 response. In an era with worrisome anti-science stances taken by national leaders in a number of countries and where critical policy and programmatic decisions are made on the basis of complex statistical tabulations that are increasingly contentious, the need for transparency and clarity in official agencies’ reporting of statistical information to the public is increasingly urgent. Improved statistical reporting at the local level is crucial because local data collection and reporting are the foundation for state and national reporting and formulation of strategic response.

The immediate challenge is to better configure communication on patterns of COVID-19 transmission and consequences of COVID-19 illness to the public – because this is the most powerful and, for the moment, only tool available in the battle.

However, there are also long-run reasons for improvement. To sustain sound, functional democracy in the 21st century where so many decisions are based on analysis of a torrent of statistical data, it is necessary to find effective ways to generate and disseminate information to “the public”. This requires thoughtful presentation of relevant and reliable information to diverse audiences within the general public (such as language minorities, and in regions such as the San Joaquin Valley, the farmworker households and local civic activists) to enhance their ability to make significant, positive contribution to the collective efforts to suppress the pandemic – even as vaccine(s) and better treatments become available.

There are now opportunities to reboot U.S. national response to the COVID-19 pandemic. But the unsteady trajectory of United States official statistical agencies, CDC, HHS, FDA, and various other federal agencies (e.g. the Department of Labor’s Occupational Safety and Health Administration) in disseminating crucial statistical information on COVID-19 during the first year of the pandemic has jeopardized not only public participation in dialogue and decision-making about COVID-19 response but exacerbated inherent conflicts between economic and public health priorities.

Dysfunctional national leadership has also contributed to a cascade in which failures and distortions at the top of a hierarchical public health system were propagated downward to states, and to local government, i.e. counties, and municipalities. It is now time to transition into more effective national-state-local collaboration in confronting the pandemic.

The inconsistently and vaguely-articulated definition of “outbreaks” and “type of transmission” are cases in point. Statistical analysis and reporting need to be better linked toward hypothesis generation – toward suggesting strategic priorities and “pressure points” for more effective intervention. It is possible that county public health authorities want to leave hypothesis generation and testing to academic researchers, but in actuality, more public engagement and input, collective inquiry and a form of “crowdsourcing” for identifying action-research directions, has great promise.

Improvements in the local “feeder” system for generating and disseminating statistical information can allow stakeholders to more clearly discern the dimensions of the pandemic and respond better. Improved reliability, clarity, and precision of information from county public health departments are needed as a basis for generating deeper insights into the epidemiology of COVID-19 and in order to generate the best possible input for strategic local government response (i.e. level of funding, priority-setting, programmatic initiatives) to suppress transmission.

Although the current analysis focuses on a specific vulnerable population in a distinctive sociopolitical context (communities in California with high concentrations of immigrant farmworkers), similar issues are likely to arise in local, national, and international COVID-19 response across the globe – especially in regions and countries with a good deal of ethnic/racial diversity and/or socioeconomic disparities. Because the San Joaquin Valley has so many similarities to the situation in less-developed countries – underfunded public health agencies with limited management and professional capacity being confronted with a major crisis – lessons learned from the U.S. experience are quite relevant to global pandemic strategy.

This can be seen from the situation in Mexico – a middle-income country – where authoritarian anti-science national leadership coupled with serious mis-steps in plans for generating sound statistical data on the impact on COVID-19, has resulted in a tragically-flawed response to the pandemic. Mexico’s arrogant reliance on its Instituto Mexicano de Seguro Social (IMSS) Clinics to provide an adequate sentinel system for monitoring COVID-19 response, despite well-known shortcomings, shows the tragic consequences of statistical reporting where the official statistical data collection and reporting strategy is designed to demonstrate a convenient, preferred outcome – i.e. the minimal impact of COVID-19 [66]. Unfortunately, similar processes have threatened the integrity of the United States’ reporting on COVID-19 as President Donald Trump called for “slowing testing down” [67, 68] and antipathy toward assessments by researchers, epidemiologists and public health officials, undercut efforts to reduce transmission through use of face masks and requirements for social distancing in business, and jeopardized public trust in potential vaccines.

The analysis presented here shows that even with limited public health system resources it is not too difficult to go beyond a rudimentary framework of reporting on COVID-19 in local jurisdictions to provide a quantitative estimate of the extent of the disproportionate impact of COVID-19 among farmworkers and their families. The analysis presented here offers straightforward practical steps that can be taken to identify the specific societal factors contributing to the disproportionate impact of COVID-19 on the vulnerable population of farmworkers and their families.

The analysis of cumulative incidence of COVID-19 in farmworker communities also shows that the “impact” of COVID-19 on the vulnerable population of farmworkers, is not fully captured by analyzing race/ethnic disparities. The analysis identifies several specific socioeconomic factors that need to be well understood and urgently addressed to assure optimal response: work in an essential industry, overcrowded housing, lack of access to testing due to maldistribution of testing sites, and hesitation within the population to secure testing and/or health care due to the lack of economic support and wraparound services to make self-isolation or quarantine viable for undocumented workers ineligible for pandemic assistance.

This sort of analysis of the situation in the San Joaquin Valley and other areas of labor-intensive agricultural counties in California and across the U.S. shows that reporting on COVID-19 as it affects a particular vulnerable population such as farmworkers does not entail untoward burden. It is technically feasible without undue expenditure – based on identifying farmworker communities and looking at the impact COVID-19 has had on each.

California took a bold and innovative step forward in October by instituting its new “health equity” metric as a factor in state approval of counties’ “opening up” for less-intensive social distancing in businesses. This will hopefully nudge recalcitrant local government toward serious, proactive efforts to generate better data and to analyze those data and deploy insights based on those analyses to improve response. They will need technical assistance in doing this. However, even with serious state and local budget pressures from the pandemic, there remains unallocated federal funding for emergency response to COVID-19 and, hopefully, a new federal administration that places a greater emphasis on public safety will pitch in to assist also.

It is unfortunate that 2020 has been a year in which the ongoing conflict between scientifically-driven decision-making popular demand for relaxation of the “non-pharmaceutical” intervention measures that were necessary to manage the COVID-19 pandemic has been so intense. This ideological conflict has been incorrectly framed by anti-science politicians as one that pits “technocracy” against “democracy”. But, the debate can be more usefully re-framed as dialogue as to how one strand of evidence-based decision-making, in this specific case, statistical reporting, can be improved so as to better contribute to the collective and widely-embraced objective of meaningfully engaging the full spectrum of community members, in this case, not just the elite, but also Latino/a farmworkers, their families, and the civic activists and local leaders in their communities, in empirically-based, rational discussion of the best practical strategies to confront COVID-19.

To accomplish this, it will be important to keep in mind that the hoped-for panacea of a COVID-19 vaccine will not provide an immediate solution to the COVID-19 pandemic, that civic engagement will still need to play a crucial role in COVID-19 response. Dr. Anthony Fauci, Director of the National Institute for Allergy and Infectious Diseases, a national leader in COVID-19 strategy, explained in mid-September that most of 2021 will be a year in which response strategy will require both non-pharmaceutical interventions and diligent efforts to distribute whatever vaccine becomes available and promote uptake [69].

Hopefully, farmworkers will rank high, along with other high-risk populations such as health care providers, public safety personnel, and other vulnerable populations such as the homeless and elderly residents in long-term care facilities, in national and state priorities for COVID-19 vaccination. Strategically, it will be desirable to have farmworker-oriented vaccination campaigns underway before the peak summer season of 2021 draws farmworkers back into the fields and packing sheds. New challenges and opportunities will almost certainly arise in statistical analysis and reporting progress about progress in the vaccination campaign.

As the United States and the world moves onward into the phase of fighting the COVID-19 pandemic with vaccination campaigns and improved treatment options, there is the promise that improved approaches to collecting, analyzing, tabulating, and disseminating the statistical data can have a tangible positive impact by more effectively engaging the public in public health systems operational decision-making at the local level as well as at the state and national level.