Contrasting Epidemiology of Cholera in Bangladesh and Africa.

In Bangladesh and West Bengal cholera is seasonal, transmission occurs consistently annually. By contrast, in most African countries, cholera has inconsistent seasonal patterns and long periods without obvious transmission. Transmission patterns in Africa occur during intermittent outbreaks followed by elimination of that genetic lineage. Later another outbreak may occur because of reintroduction of new or evolved lineages from adjacent areas, often by human travelers. These then subsequently undergo subsequent elimination. The frequent elimination and reintroduction has several implications when planning for cholera's elimination including: a) reconsidering concepts of definition of elimination, b) stress on rapid detection and response to outbreaks, c) more effective use of oral cholera vaccine and WASH, d) need to readjust estimates of disease burden for Africa, e) re-examination of water as a reservoir for maintaining endemicity in Africa. This paper reviews major features of cholera's epidemiology in African countries which appear different from the Ganges Delta.

Development of a Scorecard to Monitor Progress toward National Cholera Elimination: Its Application in Uganda.

In 2017, the Global Task Force for Cholera Control (GTFCC) set a goal to eliminate cholera from ≥ 20 countries and to reduce cholera deaths by 90% by 2030. Many countries have included oral cholera vaccine (OCV) in their cholera control plans. We felt that a simple, user-friendly monitoring tool would be useful to guide national progress toward cholera elimination. We reviewed cholera surveillance data of Uganda from 2015 to 2021 by date and district. We defined a district as having eliminated cholera if cholera was not reported in that district for at least 4 years. We prepared maps to show districts with cholera, districts that had eliminated it, and districts that had eliminated it but then "relapsed." These maps were compared with districts where OCV was used and the hotspot map recommended by the GTFCC. Between 2018 and 2021, OCV was administered in 16 districts previously identified as hotspots. In 2018, cholera was reported during at least one of the four previous years from 36 of the 146 districts of Uganda. This number decreased to 18 districts by 2021. Cholera was deemed "eliminated" from four of these 18 districts but then "relapsed." The cholera elimination scorecard effectively demonstrated national progress toward cholera elimination and identified districts where additional resources are needed to achieve elimination by 2030. Identification of the districts that have eliminated cholera and those that have relapsed will assist the national programs to focus on addressing the factors that result in elimination or relapse of cholera.

The cholera risk assessment in Kano State, Nigeria: A historical review, mapping of hotspots and evaluation of contextual factors.

Nigeria is endemic for cholera since 1970, and Kano State report outbreaks annually with high case fatality ratios ranging from 4.98%/2010 to 5.10%/2018 over the last decade. However, interventions focused on cholera prevention and control have been hampered by a lack of understanding of hotspot Local Government Areas (LGAs) that trigger and sustain yearly outbreaks. The goal of this study was to identify and categorize cholera hotspots in Kano State to inform a national plan for disease control and elimination in the State. We obtained LGA level confirmed and suspected cholera data from 2010 to 2019 from the Nigeria Centre for Disease Control (NCDC) and Kano State Ministry of Health. Data on inland waterbodies and population numbers were obtained from online sources and NCDC, respectively. Clusters (hotspots) were identified using SaTScan through a retrospective analysis of the data for the ten-year period using a Poisson discrete space-time scan statistic. We also used a method newly proposed by the Global Task Force on Cholera Control (GTFCC) to identify and rank hotspots based on two epidemiological indicators including mean annual incidence per 100 000 population of reported cases and the persistence of cholera for the study period. In the ten-year period, 16,461 cholera cases were reported with a case fatality ratio of 3.32% and a mean annual incidence rate of 13.4 cases per 100 000 population. Between 2010 and 2019, the most severe cholera exacerbations occurred in 2014 and 2018 with annual incidence rates of 58.01 and 21.52 cases per 100 000 inhabitants, respectively. Compared to 2017, reported cases and deaths increased by 214.56% and 406.67% in 2018. The geographic distribution of outbreaks revealed considerable spatial heterogeneity with the widest in 2014. Space-time clustering analysis identified 18 out of 44 LGAs as high risk for cholera (hotspots) involving both urban and rural LGAs. Cholera clustered around water bodies, and the relative risk of having cholera inside the hotspot LGA were 1.02 to 3.30 times higher than elsewhere in the State. A total of 4,894,144 inhabitants were in these hotspots LGAs. Of these, six LGAs with a total population of 1.665 million had a relative risk greater than 2 compared to the state as a whole. The SaTScan (statistical) and GTFCC methods were in agreement in hotspots identification. This study identified cholera hotspots LGAs in Kano State from 2010-2019. Hotspots appeared in both urban and rural settings. Focusing control strategies on these hotspots will facilitate control and eliminate cholera from the State.

The multi-sectorial emergency response to a cholera outbreak in Internally Displaced Persons camps in Borno State, Nigeria, 2017.

Introduction: In August 2017, a cholera outbreak started in Muna Garage Internally Displaced Persons camp, Borno state, Nigeria and >5000 cases occurred in six local government areas. This qualitative study evaluated perspectives about the emergency response to this outbreak. Methods: We conducted 39 key informant interviews and focus group discussions, and reviewed 21 documents with participants involved with surveillance, water, sanitation, hygiene, case management, oral cholera vaccine (OCV), communications, logistics and coordination. Qualitative data analysis used thematic techniques comprising key words in context, word repetition and key sector terms. Results: Authorities were alerted quickly, but outbreak declaration took 12 days due to a 10-day delay waiting for culture confirmation. Outbreak investigation revealed several potential transmission channels, but a leaking latrine around the index cases' house was not repaired for more than 7 days. Chlorine was initially not accepted by the community due to rumours that it would sterilise women. Key messages were in Hausa, although Kanuri was the primary local language; later this was corrected. Planning would have benefited using exercise drills to identify weaknesses, and inventory sharing to avoid stock outs. The response by the Rural Water Supply and Sanitation Agency was perceived to be slow and an increased risk from a religious festival was not recognised. Case management was provided at treatment centres, but some partners were concerned that their work was not recognised asking, 'Who gets the glory and the data?' Nearly one million people received OCV and its distribution benefited from a robust infrastructure for polio vaccination. There was initial anxiety, rumour and reluctance about OCV, attributed by many to lack of formative research prior to vaccine implementation. Coordination was slow initially, but improved with activation of an emergency operations centre (EOC) that enabled implementation of incident management system to coordinate multisectoral activities and meetings held at 16:00 hours daily. The synergy between partners and government improved when each recognised the government's leadership role. Conclusion: Despite a timely alert of the outbreak, delayed laboratory confirmation slowed initial response. Initial responses to the outbreak were not well coordinated but improved with the EOC. Understanding behaviours and community norms through rapid formative research should improve the effectiveness of the emergency response to a cholera outbreak. OCV distribution was efficient and benefited from the polio vaccine infrastructure.

The reactive vaccination campaign against cholera emergency in camps for internally displaced persons, Borno, Nigeria, 2017: a two-stage cluster survey.

INTRODUCTION: In 2017, amidst insecurity and displacements posed by Boko Haram armed insurgency, cholera outbreak started in the Muna Garage camp for Internally Displaced Persons (IDPs) in Borno State, Nigeria. In response, the Borno Ministry of Health and partners determined to provide oral cholera vaccine (OCV) to about 1 million people in IDP camps and surrounding communities in six Local Government Areas (LGAs) including Maiduguri, Jere, Konduga, Mafa, Dikwa, and Monguno. As part of Monitoring and Evaluation, we described the coverage achieved, adverse events following immunisation (AEFI), non-vaccination reasons, vaccination decisions as well as campaign information sources. METHODS: We conducted two-stage probability cluster surveys with clusters selected without replacement according to probability-proportionate-to-population-size in the six LGAs targeted by the campaign. Individuals aged ≥1 years were the eligible study population. Data sources were household interviews with vaccine card verification and memory recall, if no card, as well as multiple choice questions with an open-ended option. RESULTS: Overall, 12 931 respondents participated in the survey. Overall, 90% (95% CI: 88 to 92) of the target population received at least one dose of OCV, range 87% (95% CI: 75 to 94) in Maiduguri to 94% (95% CI: 88 to 97) in Monguno. The weighted two-dose coverage was 73% (95% CI: 68 to 77) with a low of 68% (95% CI: 46 to 86) in Maiduguri to a high of 87% (95% CI: 74 to 95) in Dikwa. The coverage was lower during first round (76%, 95% CI: 71 to 80) than second round (87%, 95% CI: 84 to 89) and ranged from 72% (95% CI: 42 to 89) and 82% (95% CI: 82 to 91) in Maiduguri to 87% (95% CI: 75 to 95) and 94% (95% CI: 88 to 97) in Dikwa for the respective first and second rounds. Also, coverage was higher among females of age 5 to 14 and ≥15 years than males of same age groups. There were mild AEFI with the most common symptoms being fever, headache and diarrhoea occurring up to 48 hours after ingesting the vaccine. The most common actions taken after AEFI symptoms included 'did nothing' and 'self-medicated at home'. The top reason for taking vaccine was to protect from cholera while top reason for non-vaccination was travel/work. The main source of campaign information was a neighbour. An overwhelming majority (96%, 95% CI: 95% to 98%) felt the campaign team treated them with respect. While 43% (95% CI: 36% to 50%) asked no questions, 37% (95% CI: 31% to 44%) felt the team addressed all their concerns. CONCLUSION: The campaign achieved high coverage using door-to-door and fixed sites strategies amidst insecurity posed by Boko Haram. Additional studies are needed to improve how to reduce non-vaccination, especially for the first round. While OCV provides protection for a few years, additional actions will be needed to make investments in water, sanitation and hygiene infrastructure.

Cultural influences behind cholera transmission in the Far North Region, Republic of Cameroon: a field experience and implications for operational level planning of interventions.

INTRODUCTION: In recent years, the Far North Region of Cameroon has experienced serious and recurrent cholera outbreaks. Yet, understanding of cultural influences on outbreaks and spread remain poorly understood. This qualitative study explored cultural influences on cholera exposure in this region. METHODS: Interviews and group discussions were conducted in two phases. Phase I involved key informants and phase II included focus group and household discussions. Thematic techniques including word repetition, key-indigenous-terms, and key-words-in-context were used for qualitative data analysis. RESULTS: Key informants attributed cholera etiology to dirt and spread through water (caneri) and food (group eating or faire-un-rond) while group discussions attributed it to a reprimand from god and transmission through the air. Participants suggested that funerals, weddings, open defecation, and mountaintop burial might influence cholera exposure and facilitate its spread. Hospital avoidance and non-adherence with cholera treatment regimens were linked to favorable beliefs about traditional medicine (rural-urban mentality confrontation). Furthermore, a multiplicity of ethnic languages, mistrust of message sources, culture of dependency and sentimental animal husbandry were barriers to the reception of public health messages. CONCLUSION: Many participants had limited scientific knowledge about cholera etiology and transmission. The cultural practice of mountain burial seemed to explain the high cholera attack rate in the mountainous terrain compared to the floodplains. Cultural factors are likely to play important roles in the exposure to and spread of cholera. Understanding cultural context, individual and community perceptions of risk and disease may help public health agencies in response to outbreak prevention and control.

Cholera public health surveillance in the Republic of Cameroon-opportunities and challenges.

INTRODUCTION: In Cameroon, cholera has periodically resurfaced since it was first reported in 1971. In 2003, Cameroon adapted the Integrated Disease Surveillance and Response (IDSR) strategy to strengthen surveillance in the country. This study was an in-depth description and assessment of the structure, core and support functions, and attributes of the current cholera surveillance system in Cameroon. It also discussed its strengths and challenges with hope that lessons learned could improve the system in Cameroon and in other countries in Africa implementing the IDSR strategy. METHODS: Semi-structured key informant interviews, peer reviewed articles, and government record review were conducted in the Far North and Centre Regions of Cameroon. We used the matrix and conceptual framework from the World Health Organization (WHO) and Centers for Disease Control and Prevention, WHO Regional Office for Africa Technical Guidelines to frame the study. Site visits included the WHO country office, the ministry of public health (MoPH), two Regional Public Health Delegations (RPHDs), eight health districts (HDs) and health facilities (HFs) including two labs. RESULTS: Cholera surveillance is passive but turns active during outbreaks and follows a hierarchical structure. Cholera data are collected at HFs and sent to HDs where data are compiled and sent to the RPHD in paper format. RPHDs de-identify, digitalize, and send the data to the MoPH via internet and from there to the WHO. The case definition was officially changed in 2010 but the outdated definition was still in use in 2013. Nationally, there are 3 laboratories that have the ability to confirm cholera cases; the lack of laboratory capacity at HFs hampers case and outbreak confirmation. The absence of structured data analysis at the RPHD, HD, and HF further compounds the situation, making the goal of IDSR of data analysis and rapid response at the HD very challenging. Feedback is strongest at the central level (MoPH) and non-existent at the levels below it, with only minimal training and supervision of staff. In 2012, mobile phone coverage expanded to all 183 HDs and to HFs in 2014 in the Far North and North Regions. The phones improved immediate reporting and outbreak control. Further, the creation of cholera command and control centers, and introduction of laptops at all RPHDs are major strengths in the surveillance system. Completeness and timeliness of reporting varied considerably among levels. CONCLUSION: Significant milestones in the hierarchical structure towards integration and achieving early detection and rapid response in cholera surveillance are in effective use; however, some challenges exist. The surveillance system lack labs at HFs and there is no data analysis at HD level. Thus, the goal of IDSR-strategy of early detection, data analysis, and rapid response at the HD level is a challenge. Both human and material resources are needed at the HD level to achieve this goal.