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

#### Abstract

Providing the public with relevant and reliable statistical information about the impact of COVID-19 on vulnerable populations is a crucial weapon in effective public health system response. This article examines the reporting challenges confronted by local public health agencies based on a case study of farmworker communities of the San Joaquin Valley, Eastern Coachella Valley, and Salinas Valley. The analysis includes a quantitative estimate of the impact COVID-19 has on farmworker households and highlights how socioeconomic factors and housing conditions give rise to health disparities.

The importance of local data collection and reporting as the foundation for a national epidemiological tracking system is emphasized. Current shortcomings stemming from flawed national guidance and local political pressures are noted. The discussion includes detailed recommendation for improved reporting including: more systematic tabulations of available data, an expanded set of indicators to monitor public health system response, promising approaches to improve representativeness of test-derived data on COVID-19 by making it easier to access testing and support services, coupled with messaging to broaden farmworkers’ and other socio-politically marginalized populations’ willingness to seek testing. Understanding the challenges faced and lessons learned in the San Joaquin Valley region have practical implications for a wide range of countries.

## 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.1 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.2

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

• what specific information (types of data) is most urgently needed,

• at what level of analysis – e.g. overall, by county, by zipcode, population subgroups?

• who can benefit from the information – e.g. epidemiologists, health care providers, local decision makers, employers, general public, subgroups of the general public?)

• what steps are required to assure reliability of information disseminated?

• what information is necessary to assure government accountability and effective implementation of generally agreed-upon strategies.

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:

• Tabulation of COVID-19 data on mode of transmission, cumulative incidence of COVID-19, trends of new cases, hospitalization rates, and case-fatality ratios for particularly vulnerable sub-populations such as farmworkers and key age cohorts: children and youth 0–15, working-age population 16–64, elderly 65+3

• Enhanced data collection, analysis, and reporting for local communities (zipcode level analysis and sub-populations such as farmworkers) – linked to information on provision of testing, quarantine and support services, as well as quality of contact-tracing

• Assuring adequate transparency and accountability in the public health system to effectively combat COVID-19 spread, mitigate morbidity, and provide a basis for informed public input and participation in planning and decision-making

## 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].4 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].

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.5

### 7.1Poverty

Poverty is highly correlated with prevalence of COVID-19. The Los Angeles County Department of Public Health COVID-19 dashboard, a paradigm case of thoughtful local government analysis and dissemination of COVID-19 statistical information, shows COVID-19 to be more than twice as prevalent in high-poverty census tracts (> 29% HH’s below poverty line) than in low-poverty tracts (< 10% HH’s in poverty) in the county. There was, for example, (as of September 11, 2020) a cumulative incidence of 3,743 cases/100K in the high-poverty areas of Los Angeles County vs. 1,447 cases/100K in the low-poverty areas [26]. These tracts also have very high proportions of Latino, Black, and Asian households but COVID-19 prevalence appears to be more directly correlated with household income, employment in an “essential” business where social distancing is difficult, and with crowded housing than with race/ethnicity.

Farmworker households, due as much to seasonal unemployment as to low wages, often live in poverty (with about 30% of households below the federal poverty level) and are further economically-burdened by the fact that eligibility for a broad range of social program support for low-income or otherwise disadvantaged households is conditioned on immigration status.

Although inter-state farmworker migrancy has been declining over the past decade, farmworkers’economic strategies continue to require a fair amount of intra-state migrancy which also may contribute to spread due to interfacing between separate local social networks. One of the most innovative recommendations, the Centers for Disease Control (CDC) has made to agricultural employers and workers is to strive to have work crews work in “pods” to minimize cross-network mingling and potential transmission [27], but the structure of the industry makes this difficult to implement. Almost half of California farm labor employment consists of workers employed by farm labor contractors or “custom harvesters” whose specific role is to move workers from one place to another as labor demand changes. Larger agricultural producers also often operate in multiple locations and move workers from one worksite to another.

### 7.2Employment in an essential industry

Working in an “essential” occupation where social distancing is not easily achieved and is, at best, somewhat inconsistent, is another risk factor contributing to COVID-19 transmission and prevalence among farmworkers. There are now numerous news accounts and case studies indicating how the distinctive conditions of employment as a farmworker, which include transportation arrangements (in crowded cars, vans, or buses), close contact on work breaks due to lack of shade, and congregate housing for H-2A guestworkers [28, 29, 30, 31, 32] lead to outbreaks. Much attention has been given to the very high risks of COVID-19 infection experienced by guestworkers but it is important to recognize that multiple factors contribute to COVID-19 spread in the farmworker population and that the impact of COVID-19 on local agricultural workers is also very high.

It is important to note here that U.S. agricultural producers’ reliance on guestworkers – mostly Mexican workers admitted to work in U.S. agriculture under longstanding provisions in immigration law (commonly referred to as H-2A, the type visa issued to them) – varies greatly from region to region in the country. Although the H-2A guestworkers make up only 10% of the U.S. farm labor force, their risk of COVID-19 infection is particularly high due to the Department of Labor’s requirement that employers provide them with housing. In order to comply as cost-effectively as possible, almost all housing provided by employers is congregate housing – where, typically, a number of workers share bedrooms or sleep in barracks-style quarters, as well as sharing cooking facilities and bathrooms. California’s reliance on guestworkers is lower than other major agricultural regions in the U.S. but there have been numerous reports of outbreaks in this sub-population in California agriculture [33].

Farmworkers are not alone in facing higher risks of SARS-CoV-2 infection due to work environment but, more than workers in many other essential industry sectors, they are confronted with employment conditions where employer compliance with a range of regulatory requirements, including those related specifically to COVID-19, varies greatly. The problems faced by farmworkers in the midst of the COVID-19 pandemic stem less from low earnings per se, than from uneven access to work-related benefits including sick leave, vacation leave, health insurance, other fringe benefits, and eligibility for government assistance.

Many reports have appeared documenting uneven efforts by agricultural employers to protect their labor force from worksite infection. Some have diligently sought to decrease transmission by instituting screening and social distancing measures recommended by the CDC, the California Department of Agriculture, the California Department of Labor and Workforce Development, and industry associations such as the Strawberry Commission and the California Farm Labor Contractors’Association. However, others have disregarded this advice and, more problematically, some have actively sought to suppress information about outbreaks of COVID-19 in their workforce from circulating among their workers or being revealed to the public.

Presumably, the riskiness of working in the essential industry of agriculture varies greatly from worksite to worksite and from one crop-task to another. There are no reports about COVID-19 transmission across the full spectrum of agricultural worksites but there are now extensive reports of outbreaks in packing sheds or other work contexts (such as field-packing of lettuce) where workers are lined up working with produce on conveyer belts. These specific working conditions are very risky – since social distancing is difficult and aerosolization is probably a factor in transmission. However, there may be other “high traffic” nodes in field crop production that are especially problematic. In crops with piece-rate-based pay, for example, workers rushing to dump buckets of produce in bins may have frequent close contact with the checkers who record their production. In a range of crop-tasks there is a lot of shouting. Access to hand-washing facilities is uneven. All of these factors provide opportunities for super-spreading.

### 7.3Immigration status

More than half of California farmworkers (56%) lack legal status. Lack of status contributes indirectly to increased transmission of COVID-19 due to undocumented workers’ ineligibility for federal assistance to help out during time spent in isolation due to being infected or in quarantine due to being a close contact of an infected person. Experience to date has shown there is reluctance among undocumented farmworkers with only mild cases of COVID-19 to self-isolate and still more reluctance among asymptomatic close contacts of COVID-19 cases to self-quarantine, because those who lack legal status are ineligible for both unemployment insurance (UI) and CARES Act-funded pandemic assistance. General concern about “the government” using personal information for immigrant enforcement is also a powerful disincentive to securing testing.

The State of California has sought to address the problem of undocumented workers’exclusion from CARES Act assistance by setting up a state fund to provide assistance to households excluded from federal aid. But the initial funding ($75 million from the state, matched with$50 million from California philanthropy) was very rapidly exhausted [34] since there are about 1.75 million undocumented workers in California [35]. A number of streams of local philanthropic response have vigorously engaged in local fundraising to help address the problem of inequity due to immigration status and have made important contributions but the problem of economic pressures contributing to continuing work by COVID-19+ farmworkers persists and reluctance to seek testing continues to be a serious problem.

### 7.4Lack of health insurance and a “Medical Home”

Agricultural employers are required to offer their permanent employees health insurance but this does little to help seasonal farmworkers and many low-income workers who often decline employers’ offer of health insurance because co-payments are unaffordable for them and ACA-subsidized coverage is only available to those with legal status. Because farmworkers are economically-strapped almost half (43%) lack health insurance and almost one-third (30%) had not visited a U.S. health care provider during the 2 years before they were surveyed in NAWS [36].

### 7.5Crowded Housing: Large Families and “Joint Dwellings”

One of the most distinctive and serious factors contributing to the prevalence of COVID-19 among farmworkers (and other low-income immigrants) is crowded housing where it is almost impossible for a COVID-19-positive individual to self-isolate [37, 38]. Research in a Latino immigrant neighborhood of San Francisco’s Mission District from the University of California-San Francisco (UCSF), by relying on genotyping of the specificviral strains of infected individuals (an approach now being used more extensively in case investigation), provides a definitive demonstration of the extent of household transmission in crowded housing; 65% of COVID-19-positive individuals were infected with the same strain as their housemates [39].

NAWS data provide solid information on the proportion of farmworker housing that is crowded (> 1 person/room) with 33% of farmworkers to be living in crowded housing in contrast to 2.4% of U.S. households [40]. And the farmworker households are larger – averaging 5.1 persons/HH on the average vs. 2.7 person/HH for the average U.S. household.

In one of the major labor-intensive agriculture regions within California, the Salinas Valley, 93% of farmworkers are living in crowded housing. There is, during harvest season, an average of 7.1 persons per household, and more than half (54%) of the households are “joint dwellings”, i.e. family members plus unrelated co-habitants [41]. This strategy of “doubling up” so as to be able to afford a place to live is ubiquitous in farmworker communities throughout the San Joaquin Valley and California. Research conducted in late 2018 throughout the San Joaquin Valley among Latino 1st and 2nd generation immigrants, many of whom are farmworkers, to assess the extent of differential census undercount in Census 2020, showed that about 20% lived in “complex households” (multiple families under one roof) or “complex compounds” (a primary housing unit with additional “unconventional” housing units at the address [42].

### 7.6Sociocultural factors

The Mexican and Central American immigrants who make up the overwhelming majority of the U.S. farm labor force have constrained access to information on COVID-19 transmission and health consequences – because so many have very limited schooling and confront linguistic barriers to accessing the full range of information about COVID-19. Almost half of California farmworkers (46%) have only attended elementary school while 42% read no English, and 27% have only limited English-language reading ability [36].

Basic information on COVID-19 is now widely available in Spanish and even in some of the main Mexican indigenous languages (Mixtec, Zapotec, Triqui) but the population is not very print-oriented. Nonetheless, word-of-mouth, outreach by community organizations, Spanish-language radio and TV coverage, have all attempted to promote the importance of wearing face covering, social distancing, and hand-washing – but working/housing conditions still constrain behavior [43]. Farmworkers lacking information on health consequences of COVID-19 illness (omitted from the CDC basic “educational” materials) are likely to have attenuated awareness and aspirations about the utility of taking precautions to avoid COVID-19.

## 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.6

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.

##### Table 1

Ratio of cumulative confirmed COVID-19 Cases/100K population in Fresno County farmworker towns to overall county and California (September 11–19, 2020)

 Column ref # 1 2 3 4 5 6 7 TOWNS: % farmworkers Average household size Population Cases per 100K in community Cases per 100K in county Community to county ratio Community to state ratio Testing per 100K Cumulative # of cases West Side sub-region 91,768 4,041 2,602 1.7 2.2 17,614 3,709 Cantua Creek 63% FW HHsize = 3.2 940 3,830 2,602 1.5 2.0 16,054 36 Tranquility 54% FW, HHsize = 3.3 1,173 2,813 2,602 1.1 1.5 12,276 33 Huron 53% FW, HHsize = 4.0 7,260 5,207 2,602 2.0 2.7 14,132 378 Mendota 53% FW, HHsize = 4.2 12,727 7,174 2,602 2.8 3.8 21,757 913 San Joaquin 45% FW, HHsiz = 3.8 4228 4,541 2,602 1.7 2.4 19,702 192 Firebaugh 36% FW, HHsize = 3.8 10,395 3,127 2,602 1.2 1.6 11,236 325 Laton 30% FW, HHsize = 3.6 3,541 3,361 2,602 1.3 1.7 15,250 119 Raisin City 23% FW, HHsize = 4.1 426 6,103 2,602 2.3 3.2 21,127 26 Biola 16% FW, HHsize = 4.4 949 5,901 2,602 2.3 3.1 19,705 56 Riverdale 33% FW, HHsize = 3.9 6,323 3,701 2,602 1.4 2.1 12,668 234 Caruthers 24% FW, HHsize = 3.6 5,586 4,368 2,602 1.7 2.3 14,680 244 Kerman 23% FW, HHsize = 3.8 20,195 3,773 2,602 1.5 2.0 13,459 762 Coalinga 12% FW, HHsize = 3.1 18,025 2,169 2,602 0.8 1.1 18,086 391 East Side sub-regions 125,743 5,043 2,602 1.9 2.6 14,339 5,871 Orange Cove 46% FW, HHsiz = 4.0 9,585 7,251 2,602 2.8 3.8 20,675 695 Parlier 35% FW, HHsize = 3.8 16,914 6,208 2,602 2.4 3.3 19,952 1,050 Del Rey 34% FW, HHsize = 3.8 2,664 4,279 2,602 1.6 2.3 14,865 114 Reedley 28% FW, HHsize = 3.5 30,935 4,238 2,602 1.6 2.2 16,573 1,311 Sanger 19% FW, HHsize = 3.5 34,723 3,681 2,602 1.4 1.9 17,965 1,278 Selma 17%, HHsize = 3.6 30,922 4,602 2,602 1.8 2.4 18,608 1,423 Comparison Areas FW towns: av. 28% FW, HHsize = 3.8 217,511 4,420 2,602 1.7 2.2 16,747 9,824 Fresno Co. 10% FW, HHsize ï¿¥=ï¿¥ 3.2 1,010,120 2,602 2,602 – 1.4 19,401 26,286 California: 2.3% FW, HHsize = 3.0 39,780,000 1,971 – – – 33,312 778,400

Sources: Data on COVID-19 cumulative incidence of confirmed cases and community population from Fresno County COVID-19 dashboard on 9/11, California data from California Department of Public Health on 9/19. Community characteristics from US Census Bureau tabulation of ACS 2014-2018 data by city and census-designated place (CDP). % FW in each community rounded to nearest whole percent, HHsize rounded to nearest 1/10th.

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 #123456
CommunityPopulationConfirmed casesCases Per 100KCommunity to county ratioCommunity to state ratioTesting per 100K
Oasis 68% FW HHsize = 2.93,02031310,3644.95.842,400
Mecca 41% FW HHsize = 3.77,1744165,7992.83.323,500
Thermal 18% FW HHsize = 2.91,35916111,8476.76.7N/A
North Shore 23% FW HHsize = 3.22,8921224,2192.02.418,200
Small, predominantly FW communities14,4451,0127,0063.33.928,033
Coachella 20% FW, HHsize = 3.146,8132,5075,3552.53.026,600
Indio 11% FW, HHsize = 3.1 [100j]93,7383,4403,6701.72.124,500
Urbanized communities w/ some farmworkers140,5515,9474,2312.02.425,550
Riverside Co. 1.5% FW HHsize = 3.32,517,83052,9092,10116,400
State of CA 2.3% FW, HHsize = 3.039,780,000707,8961,77933,312

* 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.

### 8.2Variations in prevalence of COVID-19 among Fresno County farmworker communities

Although average household size is an imperfect indicator of household crowding, it accounts for a significant amount of variation in cumulative confirmed cases of COVID-19 within the stratum of farmworker communities (r2= 0.544, p< 0.000). Because ACS data is likely to under-report some of the most crowded households, the actual correlation between household crowdedness and prevalence of COVID-19 is likely to be still higher.

#### 8.2.1Reliability of testing data in fresno county farmworker towns considering “density” of testing

Fresno is currently the only county in the San Joaquin Valley region that reports level of testing by community; it will soon be required for all – a welcome development. Because the data reported in Table 1 show the cumulative number of COVID-19 tests/100K population in the farmworker towns, in the county, and in the state it is possible to calculate the ratio of “density” of testing in the farmworker towns as compared to the county and the state.

Over the course of the COVID-19 pandemic up through early September, density of testing in the Fresno County farmworker towns was at only 50% of the state level while testing in Fresno County overall was at 59% of the overall state level. Lower availability of testing increases the possibility that the reported data on positivity is not representative of the actual incidence in the overall population

The new California “Blueprint for a Safer Economy” formula for evaluating adequacy of county testing efforts is elegantly designed in that it creates a new indicator of COVID-19 prevalence (adjusted case rate) based on adjusting computation of the average number of confirmed new cases/100K population/week based on local “density” of testing (tests/100K population/week in relation to the state median level of testing). Therefore, as measured by the state indicator of “adjusted case rate” , testing at 50% the density of the overall state rate requires a correction factor of 1.2 to generate a derived estimate of actual detected cases.

#### 8.2.2Adequacy of COVID-19 response in Fresno County farmworker towns based on the California indicator of positivity

California state government expectations for positivity as a threshold for relaxing social distancing requirements is that adequacy of testing is related to % of positive cases identified from all testing. High rates of positivity are considered to be indicators of inadequate control. Initial guidance from WHO provided a benchmark of 10% positivity in testing but expectations subsequently increased. As of September 23rd, California sought to get counties to achieve a testing positivity rate of < 2% to be designated as an area with “minimal” COVID-19 prevalence.

On September 30th, Fresno County’s COVID-19 dashboard data showed that the cumulative COVID-19 positivity rate in the county over the course of the pandemic, i.e. total tests/total positive, was 9.8% – slightly better than the original WHO benchmark but (along with most California counties) below the state’s current goals. However, there was a cumulative positivity rate of 26.4% for the farmworker towns – about two-and-a half times the cumulative county-wide rate. Tabulations during the first month of such reporting (October) show the utility of these indicators as input for strategic decision-making.

The good news is that substantial improvements are indicated in overall testing in Fresno County as indicated by the indicator of current positivity among tests; by the week of September 11th, the California state tabulations show a testing positivity rate of 4.9% for Fresno County and an unadjusted case rate of 6.1 new cases/100K population/week [47].

### 8.3Eastern Coachella Valley farmworker towns

The Eastern Coachella Valley is a small sub-county area in Riverside County with intensive agricultural production and dense settlement of immigrant farmworkers. The places and cities identified as farmworker communities in the area include four small self-contained communities and two larger cities that were originally farmworker settlements but that have now grown and diversified. There are also scattered clusters of small trailer parks where farmworkers live. Analysis of the cumulative incidence of COVID-19 in the six farmworker communities in the Eastern Coachella Valley agricultural region of Riverside County in southern California shows the farmworker communities in this distinctive sub-region to have even more extensive COVID-19 spread: 2.0 to 6.7 times the cumulative incidence of COVID-19 of that reported for the overall county (columns 4 and 5). Table 2 above shows the observed pattern.

#### 8.3.1Adequacy of testing and strategic response to COVID-19 in the coachella valley

As in the case of the Fresno County farmworker communities, it can be seen that, despite vigorous efforts to improve testing access there has been less testing per 100K population in the farmworker area of Riverside County as compared to the state. Based on the cumulative data, the “density” of COVID-19 testing as of September 16 was slightly over 75% of the level achieved by the state. Cumulative testing positivity was at about 25% for the smaller, predominantly farmworker, communities and about 16% for the larger communities with a significant farmworker population but a broader occupational mix.

Within the state framework, the density of local testing, while somewhat lower than the state average, would be considered adequate and no case adjustment would be required. Notwithstanding, it should be noted that the average level of positivity is still high. As in Fresno County, in the Eastern Coachella Valley there is now progress in making testing more easily available, so that the current positivity rate was 4.8% for the week of September 23 – i.e. diminishing.

### 8.4Salinas Valley farmworker towns – and the role crowded housing plays in COVID-19 transmission

Often called the “Salad Bowl of the World”, Monterey County’s farmworker communities – part of the Salinas Valley – have experienced spikes in COVID-19 like the other communities just discussed. Here, however, there is additional evidence of the ways in which farmworker housing conditions contribute to COVID-19 spread within the Salinas Valley of Monterey County. This evidence stems from the availability of high-quality detailed data on farmworker housing generated by farmworker researcher, Richard Mines as part of his 2018 farmworker survey conducted for the Salinas Pajaro Valley Agricultural Worker Housing Survey [46]. Mines defines “joint dwellings” as housing shared by multiple households – a primary family household head by a homeowner or principal renter and “extra” people sharing space. The detailed data collected in Mines’study includes details about housing conditions among farmworkers and their families specifically – that provide valuable insights into the ways in which these sorts of living conditions affect COVID-19 transmission. The report summarizes farmworker housing conditions as follows:

Most farmworkers live with others (largely other farmworkers) who are outside their family budgetary unit. Non-related adult men and women, and non-related families were all common “joint tenants”. For the entire set of dwellings, the “extra” residents add an average of 3.2 people per dwelling. Overall, the residences averaged over 7 people per dwelling when both family and “joint” residents were combined. Sometimes, owners or renters will rent out one or more of the rooms (or other spaces) in their house or apartment. Twenty-eight percent of owners and 18% of renters rent or sublease to joint dwellers. Many people were reported as sleeping outside of bedrooms, of these 79% were adults and 21% were children. Most of these non-bedroom sleepers take their rest in the living room or the garage. (page 143, Salinas Pajaro Agricultural Worker Housing Survey).

Mines reports that 15% of the farmworkers surveyed did not have a bedroom to sleep in and slept in a kitchen or a hallway. Crowdedness also resulted in more than 5 people per bathroom – both in cases where everyone lived under the same roof and in cases where people housed in a garage or backyard trailer shared a bathroom with the householder and primary family in “the main house”. More than one-third of the households (39%) had extreme crowding – 2 or more persons per room.

Table 3 provides additional evidence of the burden of COVID-19 in farmworker communities but adds to the analysis by directly demonstrating the role that crowded housing plays in the spread of the virus.

When looking at spatial patterns of COVID-19 prevalence in the Salinas Valley, the relationship between housing conditions and COVID-19 becomes even more dramatic than in the analyses of the evidence from Fresno County and the Eastern Coachella Valley and yet again shows the disproportionate impact the pandemic is having on farmworkers, their families, and their communities. More than three-quarters of Monterey county’s COVID-19 cases are in the Salinas Valley farmworker communities identified below in Table 3. Although the impact of COVID-19 varies throughout the area it is consistently higher in the farmworker communities and in neighborhoods with a higher proportion of overcrowded joint housing.

##### Table 3

Variations in cumulative incidence of COVID-19 in the Salinas Valley in relation to prevalence of joint housing

 Salinas Valley community and neighborhood

Population# COVID-19 Cases 9-24-20% joint dwellingsCumulative cases per 100K pop.Ratio of community to county
Greenfield 9392716,39884768%5,1652.3
Salinas Southeast 9390561,0872,60063%4,2561.9
King City 9393016,63865547%3,9371.8
Chualar 939251,9136833%3,5551.6
Gonzalez 939268,30629030%3,4911.6
Salinas Northeast 9390659,4611,95027%3,2791.5
Salinas Valley FW survey 183,1947,28453%3,9801.8
Total-Monterey Co.435,8289,772N/A2,242

* Tabulation only includes communities where cell sizes of Pajaro-Salinas Valley Farmworker Survey data make it possible to reliably estimate the proportion of joint housing. Farmworker neighborhoods and communities not included in the tabulation due to small cell size (< 10 cases) are Freedom, Spreckels, and Salinas zipcodes 91733, 92901, 92905, 93901, 92905, 93901, and 95093.

Table 3 shows that relative crowdedness of housing is related to prevalence of COVID-19 providing additional evidence that within-household transmission is a major factor in spread.7

## 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.

## Acknowledgments

I am grateful to Dr. Richard Mines for sharing tabulations of data on farmworker housing conditions in the Salinas Valley that provided a basis for a detailed analysis of the relationship between crowded housing and COVID-19 prevalence. Dr. Mines also very kindly shared insights from his analysis of the distribution of indigenous farmworker households in California. I am also very grateful to Dr. Jo Ann Intili, my wife and co-trustee of the Werner-Kohnstamm Family Giving Fund, for her tireless partnership in our collaborative efforts since the pandemic began to advocate for enhanced strategies and effective interventions to combat COVID-19 in communities of farmworkers and immigrants. Ongoing dialogue with fellow researchers and community activists working on behalf of farmworkers’ and immigrants’ well-being in the midst of the pandemic has been tremendously valuable in keeping me up to date on constant developments. Here in California I am particularly grateful to Noe Paramo of California Rural Legal Assistance Foundation, Oralia Maceda of the Centro Binacional Para el Desarollo Indigena Oaxaqueño, Jorge San Juan, Cindy Quezada at the Sierra Health Foundation, Naindeep Singh of The Jakara Movement, and Dr. Sergio Aguilar-Gaxiola at the Center for Reducing Health Disparities, University of California, Davis, as well as our longtime colleagues, Greg Asbed, Marley Moynahan, Gerardo Reyes, Laura Germino, and Lucas Benitez of the Coalition of Immokalee Workers in Florida, for sharing their insights and expertise about farmworkers and COVID-19.