We demonstrate how a curfew intervention was associated with a greater negative impact of COVID-19 in non-Kuwaiti populations of lower socio-economic status compared to the Kuwaiti population due to an increased in-house contact rate under curfew. A recent study by Hamadah and colleagues further demonstrated a two-fold increased odds of death and ICU admission in the non-Kuwaiti population when compared to the Kuwaiti population in Kuwait [21]. Socioeconomic and demographic factors such as ethnicity, population density, housing conditions and education level are known to be associated with increased transmission and mortality from viral illness [22,23,24,25]. The same trend appears to be manifesting in the COVID-19 pandemic globally, with a disproportionate burden of cases and mortality in lower socioeconomic groups [10,11,12]. These are the same groups that tend to disproportionately suffer from the unintended consequences of NPIs [26, 27].
Our study is corroborated by the COVID-19 experience in Singapore. A study by Koo and colleagues evaluating a Singaporean population recommended a comprehensive intervention involving quarantine, school closures and workplace distancing to reduce SARS-CoV-2 infection once community transmission was established. They did, however, note that at \( {\mathcal{R}}_0>2 \), certain dense residential clusters in Singapore showed strong viral persistence despite these measures and importantly, their study did not take into account migrant workers who travel daily from Malaysia to Singapore [28]. Despite very successful efforts at dealing with the initial spread of infection, a second resurgence of infections was challenging for Singapore to cope with as the majority of cases were found amongst migrant workers living in dense dormitories [29].
Another epidemiological study from Wuhan, China demonstrated a reduction in effective reproduction number of SARS-CoV-2 after introduction of quarantine and other measures from above 3·0 at baseline to less than 0·3 after March 1st [30]. Historically, early implementation of multiple interventions are associated with reduced disease transmission and death rates [8]. While there is clear epidemiological rationale supporting quarantine as a measure for limiting viral transmission, the evidence base continues to be weak due to difficulties in carrying out such studies [31]. Some data has suggested that while home quarantine can reduce community spread, it may also lead to an increase in infection of co-habitants [31,32,33]. In the current epidemic, the attack rate of SARS-CoV-2 in households appears to be in the range of 10-16%; however, little is known about the socioeconomic factors of these households, and we would expect higher attack rates in crowded living conditions [34,35,36].
In our study, after the institution of a partial lockdown, there was a rise in \( {\mathcal{R}}_e \) of non-Kuwaitis as well as a greater variability in the confidence interval. This may be explained by Kuwaitis and non-Kuwaitis of higher socioeconomic status having greater ability to stay at home and institute a measure of physical distancing within their homes. On the other hand, workers who are more likely to live in crowded dormitories were now spending more time in close proximity in indoor environments without wearing masks. Had migrant workers been able to physically distance themselves and effectively practiced universal masking, the incidence of infection could have decreased. However, cohabitants who were shift workers could no longer stagger their time at home as a direct result of the partial lockdown and were forced into closer proximity. This, in addition to threats to food and livelihood security, likely inflamed the situation [37]. Indeed, recent evidence based on spatiotemporal data suggested that the exponential phase of the epidemic started in late March, after the lockdown was in place [38]. The same study highlighted the benefits of introducing spatially heterogeneous interventions whereby additional control measures were localized to the migrant hotspots resulting from the partial lockdown.
Another important observation is the modest decrement in \( {\mathcal{R}}_e \) in Kuwaitis after the lockdown. For such an extreme measure with such significant economic connotations, we would have expected a greater effect, such as a reduction of \( {\mathcal{R}}_e \) below 1·0, which signals a receding disease transmission among Kuwaitis. This may be explained by the proximity of Kuwaitis and non-Kuwaitis, even throughout the lockdown [24, 25]. Given that many non-Kuwaitis provide essential services to the country, there is a strong possibility that infection was transmitted to Kuwaiti nationals despite lockdown measures in place. It follows from this that disparities within a population lead to worsening of disease transmission for all components of society, a more prolonged pandemic phase and potentially heavier impacts on the economy as a whole. We hypothesize that more equitable societies are likely to fare better (and more predictably) in this pandemic than less equitable ones.
Significant attempts were made to ease the burden of COVID-19 in non-Kuwaiti populations. Healthcare was declared free of charge for non-Kuwaitis with COVID-19 [39], funds were raised to support families and workers affected by the pandemic and field hospitals and quarantine facilities were established in the most densely populated areas. Importantly, the crisis has led to a heightened media focus on human trafficking and labor laws as important culprits in the poor living conditions of workers. This has resulted in a two-pronged government policy: pursue and punish lawbreakers, and provide amnesty and repatriation for workers trapped without valid papers [37, 38, 40]. These attempts came to national attention during the pandemic to help limit disease spread by caring for vulnerable populations and supporting a more general public health framework.
Limitations
Our modeling results should be interpreted qualitatively rather than taken as projections of the epidemic curve and associated burdens such as mortality. Models are simplifications of a complex reality which, in our case, is concerned with an emergent and complex infectious disease. Tackling such a complexity in a meaningful way requires both a sufficient understanding of the disease dynamics and sustainable access to a range of important datasets. Our analyses, however, were restricted by limitations in data availability which may be related to how data is collected and shared publicly. At the time of writing, concise information on a) daily testing rates, b) random testing, c) contact tracing and isolation, d) location, demographics and clinical manifestation of all cases was not made publicly available. Without such data, our analyses could not dissociate the effect of the infectivity of different modes of the disease from the effectiveness parameter κ. In addition, as the pandemic progressed, information about nationality became more restricted. We were unable to divide non-Kuwaiti cases into those who worked in labor and those who were more skilled with potentially higher socioeconomic status. We believe that our data largely reflects manual workers given their initial clustering in highly dense worker dormitories and areas. Finally, around 750,000 non-Kuwaitis (members of Subpopulation 2) are live-in domestic workers. However, this argues more strongly for our case, as their dilutionary effect likely blunted the calculated rise in \( {\mathcal{R}}_e \) amongst P2.
Pre-symptomatic and asymptomatic transmissions have been confirmed to play an important role in driving SARS-CoV-2 outbreaks, particularly in geographic areas where case ascertainment and testing rates or scope are low. Physical distancing mandates in such areas are believed to be an important NPI measure to control the progression of the outbreak. However, in our case, the living conditions of the migrant worker subpopulation led to a paradoxical outcome. We have not attempted to explicitly model physical distancing via compartmental subdivision within each subpopulation. Instead we chose parsimony by accounting for such a measure in terms of changes in the contact frequency as captured by the effectiveness parameter κ.
While we acknowledge that at the earliest stages of the outbreak, surveillance was mostly symptom-based, we believe that early in the outbreak the contact-tracing capacity in Kuwait may have been sufficiently effective in offsetting this and hence capturing asymptomatic cases. It is also widely acknowledged that a transparent tracking and reporting of data from random testing and contact tracing is vital for quantifying the levels of community transmission, acquired immunity and population interaction. Such unavailable data is key for informing transmission models, particularly when there is uncertainty about the relative importance of the different transmission routes of SARS-CoV-2.
