3 world, be that through campaigns or through the presence of the facility itself. <mark>Washing hands with soap (both plain and antibacterial soap) is a proven mechanism to eliminate bacteria and respiratory viruses (</mark> Luby _et al._ , 2001; Gibson _et al._ , 2002; Burton _et al._ , 2011). A systematic review of eight studies from a pool of 410 articles found that hand washing lowered the risk of respiratory infection, with risk reductions ranging from 6% to 44%, but noted that a greater number of rigorous studies are urgently needed (Rabie and Curtis, 2006). Another meta-analysis suggested that regular hand hygiene provided a significant protective effect (OR = 0.62;95% CI 0.52–0.73; I2= 0%) against 2009 pandemic influenza infection (Saunders-Hastings _et al._ , 2017). A <mark>randomized controlled trial among squatter settlements in Karachi, Pakistan, found that children younger than 5 years old living in households that were assigned to antibacterial soap had roughly a 50 percent lower incidence of pneumonia than controls (</mark> Luby _et al._ , 2005 <mark>). Similarly, another randomized control trial across 60 elementary schools in the Arab Republic of Egypt found that a hand hygiene intervention campaign significantly reduced the incidence of laboratory-confirmed influenza by 50 percent and subsequently absenteeism among the students caused by the illnesses</mark> (Talaat _et al._ , 2011). In Bangladesh, <mark>a study over 60,000 low-income households found that across the sample, respiratory illness was lower among people who had soap and water present in the hand washing station than among those who did not</mark> (Najnin _et al._ , 2019 <mark>). A two-stage cluster RCT with 60 villages in Kenya also showed that</mark> children <mark>in schools</mark> wher <mark>e hand washing and drinking water stations</mark> were mad <mark>e available were consistently less likely to have an acute respiratory infection over the following 2-10 months than in schools without (2% versus 3%, Estimated Difference in Medians -2%, 90% CI-3% to -1% in rounds 1-17) (</mark> Hoekstra _et al._ , 2012).

Taken together, it is therefore plausible that handwashing could impact the number of hospitalizations and deaths from COVID-19 via two pathways: 1) by reducing transmission and incidence of COVID-19 and 2) by reducing the incidence of underlying respiratory illness in a population, thereby reducing susceptibility to severe COVID-19. If a host who becomes infected with SARS-CoV-2 already has a respiratory infection, the chances of that developing to severe COVID-19 disease are increased. What we focus on in the analysis presented in this paper is therefore the second, more indirect pathway described above, to impact on prevalence of severe COVID-19 cases.

This study contributes to the literature in three main ways. First, it contributes to the growing body of spatially disaggregated approaches to COVID-19, but focusing on clinical risk data. Spatially disaggregated models thus far have made use of mobility data to examine transmission dynamics (Mu, Yeh and Zhang, 2021; Zachreson _et al._ , 2021) and examined the impact of government policies (Guaitoli and Pancrazi, 2021), through lockdowns, or compared population characteristics in their response to government measures (Macharia, Joseph and Okiro, 2020; Gauvin _et al._ , 2021). However, to the best of our knowledge, this study is one of the few, particularly in the Sub-Saharan African context, that have used available spatially disaggregated data on clinical risk factors to map underlying risk of severe COVID-19 in a population. Understanding spatial variation in risk using spatial modeling has proved useful for a number of diseases including malaria (Weiss _et al._ , 2019), schistosomiasis (Sturrock _et al._ , 2013) , and HIV ((Dwyer-Lindgren _et al._ , 2019). In turn, clinical risk for severe COVID-19 is likely to differ across a country, so using a spatial approach has potential to be strategically useful for targeting a health policy response. Its application to severe COVID-19 risk factors is therefore applied here.