Use of Sat Scan for Identification of Cholera Hotpots in a High-Density Suburb of Harare, Zimbabwe.


 Background: The cholera pandemic remains a major public health risk in developing nations most of which are in the Sub Saharan regions. However, there is limited data on near real time analysis using the Sat Scan whichIn this study, of particular concern is the spatial-temporary distribution of cholera cases obtained from the mapping and detection of cholera hotspots or clusters in Budiriro on the outbreak, which occurred in September 2018. Methods: The research study used the spatial geographical distribution approach in order to study the clusters of high diseases incidence in Budiriro high-density suburb of Harare, Zimbabwe. The participants in this study included patients from all age groups and gender who were either suspects or confirmed cases of cholera according to the line lists provided by Harare City Health Department. Data was then analysed using the Python, Geographic Information Systems (GIS) and the Sat-Scan. Since this study, is an essential part of the health-needs assessment in the identification of high-risk areas for a disease, understanding the characteristics of high-risk areas was needed to indicate areas, which required improvements in the provision of WASH programmes in order to reduce the risk of cholera outbreaks. Results: The results from this study showed significant clusters or hotspots of cholera in Budiriro for the period of the outbreak (29 September-02 October 2019). People within 0.22km and 0.55km showed a significant risk of being susceptible to cholera (p=0.001). Clusters 1-3 were considered to be hotspots (p<0.05) for cholera outbreak and correspondingly there were more cases of cholera. These hotspots were linked to contaminated water sources (HA034, HA039 and HA075). Water was contaminated from low flow rate of sewage. Conclusions: Cholera and other general infectious disease surveillance can benefit from this perspective approach by monitoring outbreaks in real-time as new data becomes available. The results emphasised on the importance of focusing surveillance on emerging and active clusters during epidemics. Further we concluded that safe water provision could reduce the risk of such outbreaks if Sat-scans could be applied in locating possible areas of contamination.


Results:
The results from this study showed signi cant clusters or hotspots of cholera in Budiriro for the period of the outbreak (29 September-02 October 2019). People within 0.22km and 0.55km showed a signi cant risk of being susceptible to cholera (p=0.001). Clusters 1-3 were considered to be hotspots (p<0.05) for cholera outbreak and correspondingly there were more cases of cholera. These hotspots were linked to contaminated water sources (HA034, HA039 and HA075). Water was contaminated from low ow rate of sewage.
Conclusions: Cholera and other general infectious disease surveillance can bene t from this perspective approach by monitoring outbreaks in real-time as new data becomes available. The results emphasised on the importance of focusing surveillance on emerging and active clusters during epidemics. Further we concluded that safe water provision could reduce the risk of such outbreaks if Sat-scans could be applied in locating possible areas of contamination.

Background
Cholera is a major public health problem in Sub-Saharan Africa were sanitation and safe water provision is reported as a challenge [1]. Zimbabwe particularly has had challenges of being unable to control cholera outbreaks due to lack of adequate provision of Water, Sanitation and Hygiene (WASH) programmes [2].The country has been reported to be reactive to the outbreaks of cholera and other diarrhoeal diseases [2]. WASH programmes are actived during the outbreaks and thereafter, complacency has been reported [2]. Zimbabwe reported 98592 cases of cholera, including 4288 deaths during the 2008-2009 cholera outbreak [3].
Cholera is viewed as a trans-boundary communicable disease that requires complex interventions in terms of preparedness and response, management, prevention and mitigation [4]. The devastating 2008 to 2009 cholera outbreak in Zimbabwe resulted in the neighbouring countries being affected and reported isolated outbreaks of Cholera [5]. The affected countries from the Zimbabwean outbreak included Angola, Botswana, Malawi, Namibia, South Africa, Swaziland, Zambia and the Democratic Republic of the Congo [6].
Zimbabwe has had a repeat of cholera outbreak in September 2018 [2,7]. The Ministry of Health and Child Care declared this outbreak in Harare with 11 cases having been con rmed through a rapid diagnostic test (RDT) and the clinical presentation for cholera [8]. This was mainly in a high density suburb of Harare [2,8]. This resulted in having nearly 2000 suspected cholera cases, including 58 con rmed cases and 24 deaths during the month of September 2018 [7]. However, other locations and high-density suburbs around the index suburb also reported cases of cholera during the same period [7].
This outbreak pointed to inadequate supply of WASH programmes and possible contamination of water sources in the suburbs of Harare and surrounding cities [7]. In Zimbabwe there are no studies that were performed using the near real time data that could characterise and reveal the spatial temporary distribution of cholera outbreaks. Therefore, this study sought to utilise geospatial approach in detecting and mapping the cholera outbreak in Budiriro high-density suburb in Harare, Zimbabwe.

Study settings
The study was conducted in Budiriro high-density suburb of Harare, Zimbabwe. This was the epicentre of

Study Design And Participants
This study followed a geospatial distribution approach. This was designed to identify cases according to their location in the high-density suburb of Budiriro in Harare. We made use of the line listing which was provided by the Harare City Health Department allow for secondary analysis. The line list consisted of 600 cases who were suspects or con rmed cases of cholera. These had been reported from the 1st of September 2018 to the 4th of October 2018. The cases consisted of children who were above 2 years and adults aged 21 years to 63 years. These were either suspects or cases of cholera. A case of cholera is a con rmed case from isolation of vibrio cholera 01 or 0139 from the patient with diarrhoea [6,9]. The suspected case of cholera is any individual; in areas where a cholera outbreak has not been declare who is 2 years old or older presenting with acute watery diarrhoea and severe dehydration or dying from acute watery diarrhoea or in areas where a cholera outbreak is declared, any person presenting with or dying from acute watery diarrhoea [10]. These suspect cases or con rmed cases of cholera were people from all age groups and gender who were living in Budiriro during the time of the outbreak. The study received approval from Chinhoyi University of Technology and from the Harare City Health Department in order to analyse the secondary data. We obtained the line lists from the Harare City Health Department.

Statistical Analysis
We used the Microsoft Excel spreadsheet 2013 and exported it to the Jupiter NoteBook for Python for analysis. We also use the geographical information systems (GIS) for spatial distribution [11]of disease incidence and its relationship to the potential risk factor as it played a vital role in epidemiological studies such as ours. For the near real time analysis, we used the Sat-scan [12] to identify high burdened clusters.

Results
The results from this overall study analysis showed signi cant clusters or hotspots of cholera in Budiriro for the period under study. A total of 600 cases of cholera reported during the 10th of September 2018 to 2nd of October 2018 were included in the analysis. These included children and adults who all were residences of Budiriro. These were taken from the line list, which was recorded by the Harare City Health Department. We performed the Sat Scan, which reported high spatial-temporary clusters. Four high clusters purely spatial-temporary were detected and these were statistically signi cant (p < 0.05) ( Table  1).  Cartesian Coordinates Map further helped to show the geo-coordinates for the four hotspots in Budiriro suburb (Fig. 2). The google Map showed that there were three decommissioned boreholes that acted as a source of contamination. These are shown on the google map as HA034, HA039 and HA075. HA039 was in Cluster 3, HA034 was in Cluster 1 whilst HA075 was not in any Cluster for cholera. However, this borehole (HA075) acted as a source of transmission for cholera for Cluster 2 as it acted as the main source of water supply for the residences in Cluster 2 (Fig. 3). The boreholes were situated (HA039) at latitude − 17.8901 and longitude 30.9115, HA034 situated at latitude − 17.8972 and longitude 30.9366 while HA075 was at latitude − 17.8924 and longitude 30.9352. All these boreholes (HA034, HA039 and HA075) were identi ed by the Sat Scan to be less than 50metres from the sewage carriage that was reported to have a low ow rate. Within the residence, there was erratic treated water supply from council water sources. The sewage also experience frequent water shortage and had low ow rate. Borehole (HA075) was situated at the shopping centre. The shopping centre was within the residence and there were several public toilets at the shoping centre and nearer the borehole (HA075). HA039 was very close to a house (¬10 m) and falling short of being further away from a source (sewage carriage) of contamination. HA034 was in the residential area and close to sewage carriage.  We computed a Sat Scan map for the cholera hotspots which showed that Clusters 1, 2 and 3 were statistically signi cant (p < 0.05) and that there was high transmission of cholera within these clusters. Cluster 4 was not statistically signi cant (p = 0.602) (Fig. 4).

Discussion
To the authors' knowledge, studies performed using Sat Scans to identify the possible hotspots for cholera are limited to the developed nations like the UKs and the USA. The use of Sat Scans is relatively new to the study population. Our study, which sought to identify the clusters highly affected by cholera outbreak in Budiriro suburb of Harare, Zimbabwe, using the Sat Scan revealed the existence of four clusters associated with cholera outbreak. All clusters included people of all age groups and gender who had a con rmed cholera disease. The decommissioned boreholes, were identi ed as the main sources of water supply in the suburb, and were the epicentres for the cholera outbreak. These boreholes were identi ed to be closer to the sewerage carrying pipes within Budiriro suburb. It is imperative to conduct these Sat Scans in order to identify potential sources of cholera outbreak, that can play a phenomenal role in outbreak control and prevention.
Cholera outbreak is particularly very high in densely populated areas like Budiriro in Zimbabwe were our study observed that WASH programmes were inadequate leading to the high transmission of the communicable diseases. This clearly pointed to the need for ensuring that clean water supply and sanitation and hygiene programmes performed continuously could address the risk of contracting cholera. Our study corroborated with Faso [13], Campbell et al [14] and Geltings et al [15] who reported that WASH programme works on long-term prevention and control measures for improving health, reducing poverty, and improving socio-economic development as well as responding to world-wide public health emergencies and outbreaks of life-threatening diseases like cholera.
Our study revealed that there was a high risk of contracting cholera if the source of water supply for domestic use was proximal to a low ow rate sewage carriage and this was the case with cluster two, which revealed high infection rate with cholera. Low ow rate of sewage has a high risk of causing contamination of water sources for domestic use. This particularly may act as a catapult to a surge in infection rates of cholera. This nding of ours concurred with a study that was carried in Egypt [16] on time-space analysis of the single largest cholera outbreak. The study by Smallman-Raynor et al [16] in Egypt revealed that there were clusters which had a high risk of developing cholera and these were synonymous with contaminated water bodies. Another study by Rinaldo et al [17] further elaborated that most of the burden of waterborne infections is attributable to an unsafe water supply, a lack of sanitation, and poor hygienic conditions, which may affect exposure and transmission rates either directly or indirectly which was the case with the Budiriro cholera outbreak in Zimbabwe.
Although, Budiriro high-density suburb in our study reported the outbreak of cholera, there were only four clusters of epidemiological importance and these we revealed to have common risk factors, which included erratic water supply and low ow rate of sewage. Cluster analysis provides opportunities for the epidemiologists to understand possible associations between demographic and environmental exposures and the spatial distribution of diseases [18,19]. Further, the Sat Scan helped to reveal the spatial distributions of cholera cases in Budiriro high-density suburb. The identi cation of clusters of cholera hotspots in our study has helped to stratify the ecological factors inherent in the location that Page 7/9 favoured the risk of cholera outbreak. Our ndings were also echoed by Elliot et al [20], Lawson [21], Biggerri et al [22] and Lawson et al [23] who reported that a signi cant interest in spatial epidemiology lies in identifying associated risk factors which enhance the risk of infection, the so-called ecological analysis or geographic correlations studies.

Conclusion
Cholera and other general infectious disease surveillance can bene t from the Sat Scan mapping which improves near real time analysis. The Sat Scan improves case identi cation and at risk groups and environmental factors associated with the risk. Although our study was performed using the near real time analysis, it could have been bene cial to also conduct a case control analysis to identify possible risk factors for cholera. The researcher emphasises the importance of focusing surveillance on emerging and active clusters during epidemics, since these would assist in instituting preventive measures to the outbreak of cholera. Ethical approval and consent to participate We obtained approval to conduct the study from Harare City Health Department and Chinhoyi University of Technology. We did not seek ethical clearance from the Medical Research Council of Zimbabwe because we were performing a secondary analysis of data.

Competing interests
None Funding This study did not receive funding. This was purely done for academic purposes.

Consent for publication
Not applicable