Outbreak of Cholera Due to Cyclone Kenneth in Northern Mozambique, 2019

Cholera and diarrheal diseases in Cuamba District, Niassa Province, Mozambique: Systematic healthcare facility-based surveillance strengthening, characteristics of suspected cholera and diarrheal patients, and incidence of diarrheal diseases

BACKGROUND

Mozambique is one of the countries in Africa that is continuously at risk of cholera outbreaks due to poor sanitation, hygiene, and limited access to potable water in some districts. The Mozambique Cholera Prevention and Surveillance (MOCA) project was implemented in Cuamba District, Niassa Province to prevent and control cholera outbreaks through a preemptive cholera vaccination, strengthened surveillance system for cholera and diarrheal diseases, and better understanding of cholera-related healthcare seeking behavior of local populations, which may further guide the national cholera control and prevention strategies. This article presents the surveillance component of the MOCA project.

METHODOLOGY/PRINCIPAL FINDINGS

A prospective healthcare facility (HCF)-based surveillance of cholera and diarrheal disease was conducted in six HCFs in the District of Cuamba from March 2019 to December 2020. A systematic surveillance procedure has been put in place with capacity building in selected sentinel HCFs and a basic microbiology laboratory established on-site. Patients presenting with suspected cholera or other diarrheal symptoms were eligible for enrollment. Clinical data and rectal swab samples were collected for laboratory confirmation of Vibrio Cholerae and other pathogens. A total of 419 eligible patients from six HCFs were enrolled. The median age was 19.8 years with a similar age distribution between sentinel sites. The majority were patients who exhibited diarrhea symptoms not suspected of cholera (88.8%; n = 410). Among those, 59.2% (210/397) were female and 59.9% (235/392) were 15 years and above. There were 2 cholera cases, coming outside of the catchment area. The incidence of diarrheal diseases ranged from 40-103 per 100,000 population. No Vibrio cholerae was isolated among surveillance catchment population and Escherichia coli spp. (82/277; 29.6%) was the most common pathogen isolated.

CONCLUSION/SIGNIFICANCE

Efforts were made to strengthen the systematic surveillance of suspected cholera with standardised patient screening, enrolment, and diagnostics. The first basic microbiology laboratory in Niassa Province established in Cuamba District under the MOCA project needs to be integrated into the national network of laboratories for sustainability. No reports of laboratory confirmed cholera cases from the surveillance catchment area may be highly related to the pre-emptive oral cholera vaccine (OCV) mass vaccination campaign conducted in 2018 and the use of drugs by local populations prior to visiting the sentinel HCFs. Continued systematic cholera surveillance is needed to closely monitor the cholera endemicity and epidemics, and further evaluate the long-term impact of this vaccination. High incidence of diarrheal illnesses needs to be addressed with improved water, sanitation, and hygiene (WaSH) conditions in Cuamba District. Efforts integrated with the prioritization of prevention measures are fundamental for the control of cholera in the country.

Water, Sanitation, and Hygiene (WASH) Practices and Outreach Services in Settlements for Rohingya Population in Cox's Bazar, Bangladesh, 2018-2021

(1) Background: This study aimed to investigate the existing water, sanitation, and hygiene (WASH) policy and practice of the study population and strengthen the evidence base by documenting changes in the WASH policy and practice over 3 years of the Rohingya refugee humanitarian crisis, Cox's Bazar, Bangladesh. (2) Methods: A cross-sectional surveillance design was followed; the sampling of the study population included the Rohingya refugee population and neighborhood host nationals who required hospitalization soon after seeking care and enrolled into the diarrheal disease surveillance in diarrhea-treatment centers. Throughout the study period of 3 years, a total of 4550 hospitalized individuals constituted the study participants. (3) Results: Among the hospitalized Rohingya refugee population; the use of public tap water increased significantly from 38.5% in year 1 to 91% in year 3. The use of deep tube well water significantly changed from 31.3% to 8.2%, and the use of shallow tube well water reduced significantly from 25.8% to 0.4%. Households using water seal latrine were 13.3% in year 1 and increased significantly to 31.7% in year 3. ORS consumption at home changed significantly from 61.5% in the first year to 82.1% in third year. Multivariable analysis demonstrated patients' age groups at 5 to 14 years, and 15 years and more, drinking non-tube well water, soap use after using toilet, use of non-sanitary toilet facility, father's and mother's lack of schooling, and some and severe dehydration were significantly associated with the Rohingya refugee population enrolled into the diarrheal disease surveillance. (4) Conclusion: The findings indicate significant advances in WASH service delivery as well as outreach activities by aid agencies for the Rohingya refugee population living in settlements.

The challenges of dynamic vulnerability and how to assess it

Recent disasters have demonstrated the challenges faced by society as a result of the increasing complexity of disaster risk. In this perspective article, we discuss the complex interactions between hazards and vulnerability and suggest methodological approaches to assess and include dynamics of vulnerability in our risk assessments, learning from the compound and multi-hazard, socio-hydrology, and socio-ecological research communities. We argue for a changed perspective, starting with the circumstances that determine dynamic vulnerability. We identify three types of dynamics of vulnerability: (1) the underlying dynamics of vulnerability, (2) changes in vulnerability during long-lasting disasters, and (3) changes in vulnerability during compounding disasters and societal shocks. We conclude that there is great potential to capture the dynamics of vulnerability using qualitative and model-based methods, both for reproducing historic and projecting future dynamics of vulnerability. We provide examples using narratives, agent-based models, and system dynamics.

A High-Resolution Earth Observations and Machine Learning-Based Approach to Forecast Waterborne Disease Risk in Post-Disaster Settings

Responding to infrastructural damage in the aftermath of natural disasters at a national, regional, and local level poses a significant challenge. Damage to road networks, clean water supply, and sanitation infrastructures, as well as social amenities like schools and hospitals, exacerbates the circumstances. As safe water sources are destroyed or mixed with contaminated water during a disaster, the risk of a waterborne disease outbreak is elevated in those disaster-affected locations. A country such as Haiti, where a large quantity of the population is deprived of safe water and basic sanitation facilities, would suffer more in post-disaster scenarios. Early warning of waterborne diseases like cholera would be of great help for humanitarian aid, and the management of disease outbreak perspectives. The challenging task in disease forecasting is to identify the suitable variables that would better predict a potential outbreak. In this study, we developed five (5) models including a machine learning approach, to identify and determine the impact of the environmental and social variables that play a significant role in post-disaster cholera outbreaks. We implemented the model setup with cholera outbreak data in Haiti after the landfall of Hurricane Matthew in October 2016. Our results demonstrate that adding high-resolution data in combination with appropriate social and environmental variables is helpful for better cholera forecasting in a post-disaster scenario. In addition, using a machine learning approach in combination with existing statistical or mechanistic models provides important insights into the selection of variables and identification of cholera risk hotspots, which can address the shortcomings of existing approaches.

Wind disasters adaptation in cities in a changing climate: A systematic review

Wind-related disasters will bring more devastating consequences to cities in the future with a changing climate, but relevant studies have so far provided insufficient information to guide adaptation actions. This study aims to provide an in-depth elaboration of the contents discussed in open access literature regarding wind disaster adaptation in cities. We used the Latent Dirichlet Allocation (LDA) to refine topics and main contents based on 232 publications (1900 to 2019) extracted from Web of Science and Scopus. We conducted a full-text analysis to filter out focal cities along with their adaptation measures. The results show that wind disaster adaptation research in cities has formed a systematic framework in four aspects: 1) vulnerability and resilience of cities, 2) damage evaluation, 3) response and recovery, and 4) health impacts of wind disaster. Climate change is the background for many articles discussing vulnerability and adaptation in coastal areas. It is also embedded in damage evaluation since it has the potential to exacerbate disaster consequences. The literature is strongly inclined towards more developed cities such as New York City and New Orleans, among which New York City associated with Hurricane Sandy ranks first (38/232). Studies on New York City cover all the aspects, including the health impacts of wind disasters which are significantly less studied now. Distinct differences do exist in the number of measures regarding the adaptation categories and their subcategories. We also find that hard adaptation measures (i.e., structural and physical measures) are far more popular than soft adaptation measures (i.e., social and institutional measures). Our findings suggest that policymakers should pay more attention to cities that have experienced major wind disasters other than New York. They should embrace the up-to-date climate change study to defend short-term disasters and take precautions against long-term changes. They should also develop hard-soft hybrid adaptation measures, with special attention on the soft side, and enhance the health impact study of wind-related disasters.

Early detection of cholera epidemics to support control in fragile states: estimation of delays and potential epidemic sizes

BACKGROUND

Cholera epidemics continue to challenge disease control, particularly in fragile and conflict-affected states. Rapid detection and response to small cholera clusters is key for efficient control before an epidemic propagates. To understand the capacity for early response in fragile states, we investigated delays in outbreak detection, investigation, response, and laboratory confirmation, and we estimated epidemic sizes. We assessed predictors of delays, and annual changes in response time.

METHODS

We compiled a list of cholera outbreaks in fragile and conflict-affected states from 2008 to 2019. We searched for peer-reviewed articles and epidemiological reports. We evaluated delays from the dates of symptom onset of the primary case, and the earliest dates of outbreak detection, investigation, response, and confirmation. Information on how the outbreak was alerted was summarized. A branching process model was used to estimate epidemic size at each delay. Regression models were used to investigate the association between predictors and delays to response.

RESULTS

Seventy-six outbreaks from 34 countries were included. Median delays spanned 1-2 weeks: from symptom onset of the primary case to presentation at the health facility (5 days, IQR 5-5), detection (5 days, IQR 5-6), investigation (7 days, IQR 5.8-13.3), response (10 days, IQR 7-18), and confirmation (11 days, IQR 7-16). In the model simulation, the median delay to response (10 days) with 3 seed cases led to a median epidemic size of 12 cases (upper range, 47) and 8% of outbreaks ≥ 20 cases (increasing to 32% with a 30-day delay to response). Increased outbreak size at detection (10 seed cases) and a 10-day median delay to response resulted in an epidemic size of 34 cases (upper range 67 cases) and < 1% of outbreaks < 20 cases. We estimated an annual global decrease in delay to response of 5.2% (95% CI 0.5-9.6, p = 0.03). Outbreaks signaled by immediate alerts were associated with a reduction in delay to response of 39.3% (95% CI 5.7-61.0, p = 0.03).

CONCLUSIONS

From 2008 to 2019, median delays from symptom onset of the primary case to case presentation and to response were 5 days and 10 days, respectively. Our model simulations suggest that depending on the outbreak size (3 versus 10 seed cases), in 8 to 99% of scenarios, a 10-day delay to response would result in large clusters that would be difficult to contain. Improving the delay to response involves rethinking the integration at local levels of event-based detection, rapid diagnostic testing for cluster validation, and integrated alert, investigation, and response.

Modelling geographical accessibility to support disaster response and rehabilitation of a healthcare system: an impact analysis of Cyclones Idai and Kenneth in Mozambique

OBJECTIVES

Modelling and assessing the loss of geographical accessibility is key to support disaster response and rehabilitation of the healthcare system. The aim of this study was therefore to estimate postdisaster travel times to functional health facilities and analyse losses in accessibility coverage after Cyclones Idai and Kenneth in Mozambique in 2019.

SETTING

We modelled travel time of vulnerable population to the nearest functional health facility in two cyclone-affected regions in Mozambique. Modelling was done using AccessMod V.5.6.30, where roads, rivers, lakes, flood extent, topography and land cover datasets were overlaid with health facility coordinates and high-resolution population data to obtain accessibility coverage estimates under different travel scenarios.

OUTCOME MEASURES

Travel time to functional health facilities and accessibility coverage estimates were used to identify spatial differences between predisaster and postdisaster geographical accessibility.

RESULTS

We found that accessibility coverage decreased in the cyclone-affected districts, as a result of reduced travel speeds, barriers to movement, road constraints and non-functional health facilities. In Idai-affected districts, accessibility coverage decreased from 78.8% to 52.5%, implying that 136 941 children under 5 years of age were no longer able to reach the nearest facility within 2 hours travel time. In Kenneth-affected districts, accessibility coverage decreased from 82.2% to 71.5%, corresponding to 14 330 children under 5 years of age having to travel >2 hours to reach the nearest facility. Damage to transport networks and reduced travel speeds resulted in the most substantial accessibility coverage losses in both Idai-affected and Kenneth-affected districts.

CONCLUSIONS

Postdisaster accessibility modelling can increase our understanding of spatial differences in geographical access to care in the direct aftermath of a disaster and can inform targeting and prioritisation of limited resources. Our results reflect opportunities for integrating accessibility modelling in early disaster response, and to inform discussions on health system recovery, mitigation and preparedness.

The Impact of Climate Change on Vaccine-Preventable Diseases: Insights From Current Research and New Directions

Purpose of Review

Vaccine-preventable diseases remain a major public health concern globally. Climate is a key driver of the dynamics of many infectious diseases, including those that are vaccine preventable. Understanding the impact of climate change on vaccine-preventable diseases is, thus, an important public health research priority. Here, we summarize the recent literature and highlight promising directions for future research.

Recent Findings

Vaccine-preventable enteric diseases, such as cholera, exhibit sensitivity to precipitation and flooding events. The predicted increase in extreme weather events as a result of climate change could exacerbate outbreaks of these pathogens. For airborne pathogens, temperature and specific humidity have been shown to be the most important environmental drivers, although the impact of climate change on disease burden and dynamics remains unclear. Finally, the transmission dynamics of vector-borne diseases are dependent on both temperature and precipitation, and climate change is expected to alter the burden and geographic range of these diseases. However, understanding the interacting effects of multiple factors, including socioeconomic and ecological factors, on the vector-borne disease ecosystem will be a crucial step towards forecasting disease burden under climate change.

Summary

Recent work has demonstrated associations between climate and transmission of vaccine-preventable diseases. Translating these findings into forecasts under various climate change scenarios will require mechanistic frameworks that account for both intrinsic and extrinsic drivers of transmission, and the non-linear effects on disease burden. Future research should also pay greater attention to uncertainty in both the climate modeling processes as well as disease outcomes in the context of vaccine-preventable diseases.

Survey of pathogenic bacteria of biofilms in a metropolitan drinking water distribution system

Bacteria, especially pathogenic bacteria, were detected in order to estimate the safety of drinking water distribution systems (DWDSs). Sixteen biofilms and 12 water samples (six retained and six flowing) were collected from a city DWDS in eastern China. Biofilms were observed using scanning electron microscopy. Cultivable bacteria of biofilms were counted by heterotrophic plate counts, ranging from 3.61 × 101 to 1.67 × 106 CFU·cm-2. Coliforms, Salmonella, Shigella, Vibrio and Legionella were separated by Eosin-Methylene Blue (EMB) agar, Salmonella chromogenic medium, Shigella chromogenic medium, Thiosulfate Citrate Bile Salts Sucrose (TCBS) agar and Buffered Charcoal Yeast Extract (BCYE) agar and 13/16, 8/16, 7/16, 6/16, 0/16 biofilm samples were found to be positive, respectively. Retained and flowing water samples were collected to estimate the influence of hydrodynamic conditions on biofilm detachment. All six retained water samples were positive for bacteria, the count ranged from 1.2 × 103 to 2.8 × 104 CFU·mL-1 and 2/6, 3/6, 2/6, 0/6, 0/6 samples were positive for coliforms, Salmonella, Shigella, Legionella and Vibrio, respectively. While only three of six flowing water samples were bacteria positive, the counts ranged from 102 to 103 CFU·mL-1, 2/6 were coliform positive and no pathogens were detected under testing. The results show that there are pathogens in DWDS biofilms, which can cause health-related problems if detached from their surfaces.