_D -- no sewer bursts in highest (75th percentile) density burst areas. Right – the cumulative reduction (%) in cases achieved, and population targeted, from targeting wards in order of priority._

# Discussion

There are a few key findings that come out of this research and have direct policy implications. The modeling suggested that sanitation risk, poverty, sewer burst density and incidence of imported cases were all risk factors for cholera. Meanwhile, increasing geological vulnerability, distance to medium sized market, proportion with unimproved or other water source, private borehole density and distance to water network were also correlated, but negatively, meaning they acted as protective factors. The correlation of poor sanitation more generally with cholera risk [12] as well as sewer bursts are well known in the literature [20] as well as specifically being known to be an issue in the context of a previous cholera outbreak in Zimbabwe [35]. The association with poverty is also unsurprising [36]. Associated factors with poverty and market size are often identified in the literature such as population density, overcrowding and low educational status [37], [38]. The protective character of proximity to the water network is also supported by a similar study in Lusaka, Zambia [12] **.** Surprising findings from this work include the fact that proportion of those with unimproved water source is a protective factor and that increases in geological vulnerability is also a protective factor. The former can be explained by the proximity of piped water sources to sewers with a high number and density of bursts. However, the association of increased geological vulnerability with reduced cholera risk is unexpected, not substantiated in the literature and requires further exploration.

The modeling suggests that there was an interaction between the proportion of households with piped water and distance to the sewer network. In the case of Harare, it suggests that closer to the sewer network (at 0km), the risk of cholera is slightly higher, the higher the proportion of households who have piped water. However, this relationship switches direction in areas >2km from the sewer network, where the higher the proportion of households with piped water, the lower the risk of cholera. This implies that there is a higher risk of having a piped water connection for households which are proximate to the sewer network in Harare, which we believe to be due to the high rate of sewer bursts in the city at the time of the outbreak. The most accurate way of testing whether this is the case would be through water quality testing data at different points along the network. Although water quality testing data was provided for this analysis, there were insufficient data points to be able to make such a comparison. In the absence of such data, this analysis can still provide some useful insights into investments that can reduce sewer bursts particularly in areas which are closer to the piped water network, and thereby offer the greatest health benefits in terms of reducing cholera risk.

We identify that spatially, the risk of sewer bursts on this occasion was concentrated in five wards in the south west of the city. On the assumption that sewer bursts do not occur at random, but are spatially correlated due to underlying weaknesses in the network in those areas, targeting these five wards promises to reduce cases across the city by up to 70%. Using the data from the bursts reported and analyzed, there appeared to be limited benefits (in terms of reducing cholera risk) in investing in repairing sewer bursts throughout the city as it would have led to a .87 reduction in 14