Epidemic Curve Research Articles

A Review of Mpox Outbreak and Public Health Response in Spain.

In May 2022, an unprecedented Mpox outbreak was reported in several non-endemic countries with unknown epidemiological links. Since May 2022, more than 20,000 cases have been reported in Europe. Spain has been the most affected country in Europe. We aim to describe the Mpox epidemiological profile in Spain, identify its outbreak risks, and describe public health interventions implemented by the Spanish authorities. A literature review was conducted, using specific selection criteria to obtain relevant publications describing Mpox clinical presentation and risk factors and the public health response in Spain to the ongoing outbreak. 63.1% of the cases presented an anogenital rash, considered a specific and early symptom in this outbreak. Low case fatality rate is observed, mainly in risk groups, such as the immunocompromised population. Patients evolution was generally favorable, although 3-8% required hospitalization and two deaths occurred; 40% of patients were previously diagnosed with HIV infection. Most of the cases were seen among young population and concentrated in men who had sex with other men, mainly with multiple sexual partners, who did not practice safe sex such as using condoms, and those attending mass event parties. To date, the Mpox outbreak is not considered a public health emergency of international concern. The epidemiological trend of the virus in Spain shows that public health response interventions (health education, contact tracing, vaccination, etc.) have adequately controlled the epidemic curve in high-risk populations and avoided spreading the virus to other groups within the community.

Modern Statistical Methods for Infectious Diseases to Analyse Covid-19 Pandemic Data in Rwanda

The corona-virus ailment 2019(COVID-19) took tens of millions of lives and disrupted dwelling requirements at individual, societal, and international levels, causing penalties globally. Understanding its epidemic curve and Spatio-temporal dynamics is indispensable for the development of tremendous public fitness plans and responses and the allocation of resources. Thus, we performed the analysis of the epidemiological dynamics and spatio-temporal patterns of the COVID-19 pandemic in Rwanda. Using the surveillance bundle in R software version 4.0.2, we implemented endemic-epidemic multivariate time sequence methods for infectious diseases to analyze COVID-19 facts with the aid of Rwanda Biomedical Center, under the Ministry of Health, from March 15, 2020, to January 15, 2021. The COVID-19 pandemic came in waves in Rwanda and showed a heterogeneous spatial distribution across districts. The Rwandan authorities answered effectively and successively through the implementation of more than a few health measures and intervention policies to reduce the transmission of the disease. Analysis of the three factors of the mannequin confirmed that the most affected districts displayed epidemic elements inside the area, whereas the impact of epidemic elements from spatial neighbors had been skilled via the districts that surround the most affected districts. The contamination followed the disorder endemic vogue in other districts. The epidemiological and Spatio-temporal dynamics of COVID-19 in Rwanda show that the implementation of measures and interventions contributed appreciably to minimize COVID-19 transmission inside and between districts. This accentuates the essential name for endured intra-and inter-business enterprise and community engagement nationwide to make a certain effective and efficient response to the pandemic.

EPyDGGA: automatic configuration for fitting epidemic curves

Many epidemiological models and algorithms are used to fit the parameters of a given epidemic curve. On many occasions, fitting algorithms are interleaved with the actual epidemic models, which yields combinations of model-parameters that are hard to compare among themselves. Here, we provide a model-agnostic framework for epidemic parameter fitting that can (fairly) compare different epidemic models without jeopardizing the quality of the fitted parameters. Briefly, we have developed a Python framework that expects a Python function (epidemic model) and epidemic data and performs parameter fitting using automatic configuration. Our framework is capable of fitting parameters for any type of epidemic model, as long as it is provided as a Python function (or even in a different programming language). Moreover, we provide the code for different types of models, as well as the implementation of 4 concrete models with data to fit them. Documentation, code and examples can be found at https://ulog.udl.cat/static/doc/epidemic-gga/html/index.html.

Public Decision Policy for Controlling COVID-19 Outbreaks Using Control System Engineering

This work is a response to the appeal of various international health organizations and the Automatic Control Community for collaboration in addressing Coronavirus/COVID-19 challenges during the initial stages of the pandemic. Specifically, this study presents scientific evidence supporting the efficacy of three primary non-pharmacological strategies for pandemic mitigation. We propose a control system to aid in formulating a public decision policy aimed at managing the spread of COVID-19 caused by the SARS-CoV-2 virus, commonly known as coronavirus. The primary objective is to prevent overwhelming healthcare systems by averting the saturation of intensive care units (ICUs). In the context of COVID-19, understanding the peak infection rate and its time delay is crucial for preparing healthcare infrastructure and ensuring an adequate supply of intensive care units equipped with automatic ventilators. While it is widely recognized that public policies encompassing confinement and social distancing can flatten the epidemiological curve and provide time to bolster healthcare resources, there is a dearth of studies examining this pivotal issue from the perspective of control system theory. In this study, we introduce a control system founded on three prevailing non-pharmacological tools for epidemic and pandemic mitigation: social distancing, confinement, and population-wide testing and isolation in regions experiencing community transmission. Our analysis and control system design rely on the susceptible-exposed–infected–recovered–deceased (SEIRD) mathematical model, which describes the temporal dynamics of a pandemic, tailored in this research to account for the temporal and spatial characteristics of SARS-CoV-2 behavior. This model incorporates the influence of conducting tests with subsequent population isolation. An On–off control strategy is analyzed, and a proportional–integral–derivative (PID) controller is proposed to generate a sequence of public policy decisions. The proposed control system employs the required number of critical beds and ICUs as feedback signals and compares these with the available bed capacity to generate an error signal, which is utilized as input for the PID controller. The control actions outlined involve five phases of “Social Distancing and Confinement” (SD&C) to be implemented by governmental authorities. Consequently, the control system generates a policy sequence for SD&C, with applications occurring on a weekly or biweekly basis. The simulation results underscore the favorable impact of these three mitigation strategies against the coronavirus, illustrating their efficacy in controlling the outbreak and thereby mitigating the risk of healthcare system collapse.

Impact of vaccination and high-risk group awareness on the mpox epidemic in the United States, 2022–2023: a modelling study

The unprecedented global outbreak of mpox in 2022 posed a public health challenge. In addition to the mpox vaccine campaign in the United States (US), community organisations and public health agencies initiated educational efforts to promote sexual risk reduction. This modelling study estimated the impact of the two-dose vaccination campaign and sexual behaviour changes coincident with high-risk group awareness on the mpox epidemic in the US. We fitted a deterministic, risk-structured SEIARV model to the epidemic curve of reported mpox cases in the US between May 22, 2022 and December 22, 2022. We evaluated the putative effects of the two preventive responses in the US -- vaccination and sexual risk reduction -- at the population-level, by calculating the prevention percentages of cumulative cases compared to the counterfactual scenario without interventions. We performed sensitivity analyses with four parameters: case reporting fidelity, vaccine effectiveness, proportion of asymptomatic cases, and assortative mixing. Model fitting revealed a basic reproduction number of 3.88 and 0.39 for the high-risk and low-risk populations, respectively, with 71.8% of mpox cases estimated from the high-risk population. A two-dose vaccination campaign, solely, could prevent 21.2% (10.2%-24.1%) of cases, while behaviour changes due to high-risk group awareness alone could prevent 15.4% (14.3%-20.6%). The combination of both measures were synergistic, with the model suggesting that 64.0% (43.8%-69.0%) of US cases were averted that would have otherwise occurred. Our models suggest that the 2022-2023 mpox epidemic in the US was controlled by a combination of two-dose mpox vaccination campaign and high-risk group awareness and sexual risk reduction. Taiwan Ministry of Education grant #NTU-112L9004, Taiwan National Science and Technology Council grant #MOST-109-2314-B-002-147-MY3 and grant #NSC-112-2314-B-002-216-MY3. SHV was supported, in part, by US National Institutes of Health grant #P30MH062294.

Combined visualization of genomic and epidemiological data for outbreaks.

In epidemiological investigations, pathogen genomics can provide insights and test epidemiological hypotheses that would not have been possible through traditional epidemiology. Tools to synthesize genomic analysis with other types of data are a key requirement of genomic epidemiology. We propose a new 'phylepic' visualization that combines a phylogenomic tree with an epidemic curve. The combination visually links the molecular time represented in the tree to the calendar time in the epidemic curve, a correspondence that is not easily represented by existing tools. Using an example derived from a foodborne bacterial outbreak, we demonstrated that the phylepic chart communicates that what appeared to be a point-source outbreak was in fact composed of cases associated with two genetically distinct clades of bacteria. We provide an R package implementing the chart. We expect that visualizations that place genomic analyses within the epidemiological context will become increasingly important for outbreak investigations and public health surveillance of infectious diseases.

Curvas epidêmicas e o perfil de pacientes hospitalizados pela COVID-19 em região de fronteira

Objective: to describe the epidemic curves and analyze the epidemiological profile of patients hospitalized with COVID-19 in a triple border city. Method: descriptive-quantitative. The population consisted of COVID-19 cases that required hospitalization, analyzing variables such as: age, gender, race/color, city where they lived, occupation, pregnant woman, institutionalized patient and evolution. Descriptive statistical analysis and analysis of variance and chi-square tests were used. Results: four epidemic curves were identified in the studied period. Among hospitalized cases, males predominated (55%). Cure was the most frequent outcome in curves 1, 2 and 4, but with no statistical difference (p = 0.2916). Curve 3 showed a higher frequency of deaths (41.70%) in relation to cures (38.77%). The mean ages were significantly different between the curves, with curve 4 having the lowest mean age. Conclusion: it was concluded that the epidemic curves were influenced by different situations; unvaccinated population, easing of restrictive measures, reopening of the Brazil-Paraguay border, interruption of control actions, crowding of people and circulation of new variants of the disease. Through the epidemiological profile of hospitalized patients, it was concluded that being male, of mixed race/color, aged between 61 and 85 years, and being deprived of freedom were associated with hospitalization and the occurrence of death.

Epidemic curves and the profile of patients hospitalized by COVID-19 in a border region

Objetivo: describir las curvas epidémicas y analizar el perfil epidemiológico de los pacientes hospitalizados por COVID-19 en un municipio de triple frontera. Método: descriptivo-cuantitativo. La población se configuró de casos de COVID-19 que requirieron hospitalización, analizando variables como: edad, sexo, raza/color, municipio de residencia, ocupación, gestante, paciente institucionalizado y evolución. Se utilizó el análisis estadístico descriptivo y las pruebas de análisis de varianza y chi-cuadrado. Resultados: se identificaron cuatro curvas epidémicas en el período estudiado. Entre los casos hospitalizados, predominó el sexo masculino (55%). La cura fue el desenlace más frecuente en las curvas 1, 2 y 4, aunque sin diferencia estadística (p = 0,2916). La curva 3 presentó una mayor frecuencia de fallecimientos (41,70%) en relación a la cura (38,77%). El promedio de edad fue significativamente diferente entre las curvas, siendo que la curva 4 presentó el menor promedio de edad. Conclusión: se concluyó que las curvas epidémicas fueron influenciadas por diferentes situaciones; población no vacunada, flexibilización de las medidas restrictivas, reapertura de la frontera Brasil-Paraguay, interrupción de las acciones de control, aglomeración de personas y circulación de nuevas variantes. Por medio del perfil epidemiológico de los enfermos hospitalizados, se concluyó que ser del sexo masculino, de raza/color pardo, en el rango de edad de 61 a 85 años, estar privado de libertad se asociaron con la hospitalización y ocurrencia de fallecimiento.

Epidemic curves and the profile of patients hospitalized by COVID-19 in a border region

Objetivo: descrever as curvas epidêmicas e analisar o perfil epidemiológico dos pacientes hospitalizados pela COVID-19 em um município de tríplice fronteira. Método: descritivo-quantitativo. A população configurou-se de casos de COVID-19 que necessitaram de hospitalização, analisando variáveis como: idade, sexo, raça/cor, município de residência, ocupação, gestante, paciente institucionalizado e evolução. Utilizou-se a análise estatística descritiva e os testes análise de variância e qui-quadrado. Resultados: identificaram-se quatro curvas epidêmicas no período estudado. Dentre os casos hospitalizados, predominou o sexo masculino (55%). A cura foi o desfecho mais frequente nas curvas 1, 2 e 4, porém sem diferença estatística (p = 0,2916). A curva 3 apresentou uma maior frequência de óbitos (41,70%) em relação à cura (38,77%). As médias de idade foram significativamente diferentes entre as curvas, sendo que a curva 4 apresentou a menor média de idade. Conclusão: concluiu-se que as curvas epidêmicas foram influenciadas por diferentes situações; população não vacinada, flexibilização das medidas restritivas, reabertura da fronteira Brasil-Paraguai, interrupção das ações de controle, aglomeração de pessoas e circulação de novas variantes. Por meio do perfil epidemiológico dos doentes hospitalizados, concluiu-se que ser do sexo masculino, de raça/cor parda, na faixa etária de 61 a 85 anos, estar privado de liberdade se associaram com a hospitalização e ocorrência de óbito.

Interplay of missed opportunity for vaccination and poor response to the vaccine led to measles outbreak in a slum area of Eastern Mumbai, India.

In the third week of September 2022, an outbreak of measles was reported from a slum in Eastern Mumbai, India. We sought to investigate whether failure to vaccinate or vaccine failure was the cause. We constructed an epidemic curve, drew a spot map, and calculated the attack rate and case-fatality ratio. We calculated vaccine effectiveness (VE) for one and two doses of measles vaccine in an unmatched case-control study and did stratified analysis by sex, availability of vaccination card, and migrant status. We identified 358 cases and four deaths with a 11.3% attack rate and 1.1% case fatality, both being highest among 0-24-month-old boys. The epidemic curve suggested a propagated mode of spread. The VE for two doses was 64% (95% confidence interval (CI): 23-73%) among under-5-year-old children and 70% (95% CI: 28-88%) among 5-15-year-old children. Failure to vaccinate, consequent to the COVID-19 pandemic, and vaccine hesitancy might have led to the accumulation of susceptible children in the community. Additionally, the occurrence of case-patients among vaccinated suggests reduced VE, which needs further investigation into humoral and cell-mediated immunity as well as contributory factors including nutritional status. Outbreak response immunization to complete immunization of missed and dropout children was carried out to control the outbreak.

Epidemic Curves of COVID-19 in the World which are Similar Within but not Across Regions

The number of the COVID-19 patients (P), that of the deaths (D) and the case-fatality rate (D/P) were followed daily from 3 January 2020 till 22 December 2023 for countries in Western Pacific, European, American and African regions. The shape of the epidemic curves was similar within but not across the regions. The number of the patients was proportional to the population size and case-fatality rate was around 0.01 for all the countries except African countries where the number of the patients was not correlated with the population size.

First Outbreak of African Swine Fever in Sweden: Local Epidemiology, Surveillance, and Eradication Strategies

The first case of African swine fever (ASF) was confirmed in Sweden in September 2023. This article describes the local epidemiology, including the spatiotemporal dynamics of the outbreak and some of the factors that may have contributed to its apparently successful eradication. Upon detection of the outbreak, strict control measures were put in place in a preliminarily defined infected zone. A carcass search, including geo‐localisation, removal, sampling, and destruction of found carcasses, was initiated and a preliminary core area was defined based on the results. Six months after confirmation of the first case, 93 wild boar carcasses had been found in the infected zone, of which 62 tested positive for ASF virus (ASFV). All ASFV‐positive carcasses were found inside the core area. Based on two taphonomy methods, it was assumed that the infection was introduced between early May and late June 2023. The data also indicated that the epidemic curve peaked between mid‐August and mid‐September, with the last death occurring in late September 2023. Based on the average estimated time of death, geo‐localisation of carcasses and two‐dimensional kernel density estimation, clustering in space and time was identified. An online questionnaire with questions about hunting and the wild boar population was sent to all leaders of hunting groups in the infected zone. The results showed that the wild boar population had increased in the last 10 years but with large variations and geographical heterogeneity in space use. Disease introduction through natural wild boar movements was excluded and it was assumed that the long‐distance translocation of the virus had occurred through human activities. A municipal waste collection centre without wild boar‐proof fencing is located close to the epicentre of the outbreak, attracting many wild boar and contributing to the spread of the virus once it had been introduced to the population.

Dynamical analysis of a network-based SIR model with saturated incidence rate and nonlinear recovery rate: an edge-compartmental approach.

A new network-based SIR epidemic model with saturated incidence rate and nonlinear recovery rate is proposed. We adopt an edge-compartmental approach to rewrite the system as a degree-edge-mixed model. The explicit formula of the basic reproduction number $ \mathit{\boldsymbol{R_{0}}} $ is obtained by renewal equation and Laplace transformation. We find that $ \mathit{\boldsymbol{R_{0}}} < 1 $ is not enough to ensure global asymptotic stability of the disease-free equilibrium, and when $ \mathit{\boldsymbol{R_{0}}} > 1 $, the system can exist multiple endemic equilibria. When the number of hospital beds is small enough, the system will undergo backward bifurcation at $ \mathit{\boldsymbol{R_{0}}} = 1 $. Moreover, it is proved that the stability of feasible endemic equilibrium is determined by signs of tangent slopes of the epidemic curve. Finally, the theoretical results are verified by numerical simulations. This study suggests that maintaining sufficient hospital beds is crucial for the control of infectious diseases.

Classification of Territorial Entities of Colombia According to the Epidemiological Curve of Sars-Cov2 between 03-06-2020 and 02-04-2021

Classification of Territorial Entities of Colombia According to the Epidemiological Curve of Sars-Cov2 between 03-06-2020 and 02-04-2021

Using logistic function to predict epidemic trend of COVID-19 in China

As the novel coronavirus continues to spread and mutate, there has been growing concern over public health. Multiple measures have been enacted to mitigate the transmission of the disease, resulting in varying infection scenarios across different countries. To achieve timely and effective control of the epidemic, we note that predicting the future course of an epidemic plays an important role. The logistic function, a continuous-time demographic model, may be a suitable mathematical tool for estimating the trend of the epidemic. This paper aims to evaluate the accuracy of the logistic map in estimating the future trend of the COVID-19. We collect the most recent COVID-19 epidemiological data prior to January 30, 2023, and subsequently integrate figures into the curve fitting tool in MATLAB to generate an epidemic curve. By comparing the actual numbers and the predicted figures, the accuracy of logistic map can be properly assessed.

Equivalence of mass action and Poisson network SIR epidemic models

This brief note highlights a largely overlooked similarity between the SIR ordinary differential equations used for epidemics on the configuration model of a Poisson network and the classical mass-action SIR equations introduced nearly a century ago by Kermack and McKendrick. We demonstrate that the decline pattern in susceptibles is identical for both models. This equivalence carries practical implications: the susceptibles decay curve, often referred to as the epidemic or incidence curve, is frequently used in empirical studies to forecast epidemic dynamics. Although the curves for susceptibles align perfectly, those for infections do differ. Yet, the infection curves tend to converge and become almost indistinguishable in high-degree networks. In summary, our analysis suggests that under many practical scenarios, it's acceptable to use the classical SIR model as a close approximation to the Poisson SIR network model.

Seroprevalence of Anti-SARS-CoV-2 Remained Extremely Low in Taiwan Until the Vaccination Program Was Implemented.

The Taiwanese government made a concerted effort to contain a coronavirus disease 2019 (COVID-19) nosocomial outbreak of variant B.1.429, shortly before universal vaccination program implementation. This study aimed to investigate seroprevalence in the highest-risk regions. Between January and February 2021, we retrieved 10 000 repository serum samples from blood donors to examine for antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleocapsid (N) and spike (S) antigens. A positive result was confirmed if anti-N and anti-S antibodies were positive. Overall, 2000 donors residing in the highest-risk district and donating blood in January 2021 were further examined for SARS-CoV-2 RNA. We estimated seroprevalence and compared the epidemic curve between confirmed COVID-19 cases and blood donors with positive antibodies or viral RNA. Twenty-one cases with COVID-19 were confirmed in the nosocomial cluster, with an incidence of 1.27/100 000 in the COVID-affected districts. Among 4888 close contacts of the nosocomial cases, 20 (0.4%) became confirmed cases during isolation. Anti-SARS-CoV-2 was detected in 2 of the 10000 blood donors, showing a seroprevalence of 2/10000 (95% CI, 0.55-7.29). None of the 2000 donors who underwent tests for SARS-CoV-2 RNA were positive. The SARS-CoV-2 infection epidemic curve was observed sporadically in blood donors compared with the nosocomial cluster. In early 2021, an extremely low anti-SARS-CoV-2 seroprevalence among blood donors was observed. Epidemic control measures through precise close contact tracing, testing, and isolation effectively contained SARS-CoV-2 transmission before universal vaccination program implementation.

Transmission of COVID-19 in the presence of single-dose and double-dose vaccines with hesitancy: mathematical modeling and optimal control analysis

IntroductionThe unexpected emergence of novel coronavirus identified as SAR-CoV-2 virus (severe acute respiratory syndrome corona virus 2) disrupted the world order to an extent that the human activities that are core to survival came almost to a halt. The COVID-19 pandemic created an insurmountable global health crisis that led to a united front among all nations to research on effective pharmaceutical measures that could stop COVID-19 proliferation. Consequently, different types of vaccines were discovered (single-dose and double-dose vaccines). However, the speed at which these vaccines were developed and approved to be administered created other challenges (vaccine skepticism and hesitancy).MethodThis paper therefore tracks the transmission dynamics of COVID-19 using a non-linear deterministic system that accounts for the unwillingness of both susceptible and partially vaccinated individuals to receive either single-dose or double-dose vaccines (vaccine hesitancy). Further the model is extended to incorporate three time-dependent non-pharmaceutical and pharmaceutical intervention controls, namely preventive control, control associated with screening-management of both truly asymptomatic and symptomatic infectious individuals and control associated with vaccination of susceptible individuals with a single dose vaccine. The Pontryagin's Maximum Principle is applied to establish the optimality conditions associated with the optimal controls.ResultsIf COVID-19 vaccines administered are imperfect and transient then there exist a parameter space where backward bifurcation occurs. Time profile projections depict that in a setting where vaccine hesitancy is present, administering single dose vaccines leads to a significant reduction of COVID-19 prevalence than when double dose vaccines are administered. Comparison of the impact of vaccine hesitancy against either single dose or double dose on COVID-19 prevalence reveals that vaccine hesitancy against single dose is more detrimental than vaccine hesitancy against a double dose vaccine. Optimal analysis results reveal that non-pharmaceutical time-dependent control significantly flattens the COVID-19 epidemic curve when compared with pharmaceutical controls. Cost-effectiveness assessment suggest that non-pharmaceutical control is the most cost-effective COVID-19 mitigation strategy that should be implemented in a setting where resources are limited.DiscussionPolicy makers and medical practitioners should assess the level of COVID-19 vaccine hesitancy inorder to decide on the type of vaccine (single-dose or double-dose) to administer to the population.

SARS-CoV-2 rapid antigen testing positive rate in community testing stations as an indicator for COVID-19 epidemic trend, Taipei, Taiwan, May to August 2021

BackgroundReal-time surveillance of COVID-19 in large-scale community outbreaks presents challenges. Simple counts of the daily confirmed cases can be misleading due to constraints from bottlenecks in access to care or laboratory testing. This study aimed to investigate the role of the SARS-CoV-2 antigen rapid diagnostic test (Ag-RDT) in addressing these challenges for real-time COVID-19 surveillance. MethodsThis study included the results of 86,933 SARS-CoV-2 Ag-RDT and real-time reverse transcription polymerase chain reaction (RT-PCR) tests. These were conducted at four community testing stations within the Taipei metropolitan area during a community COVID-19 outbreak spanning from May 17, 2021, to August 9, 2021. We examined the correlation between the positive rates of Ag-RDT tests and the epidemic curve of laboratory-confirmed COVID-19 cases by onset date to examine its role in real-time surveillance. ResultsDuring the 85-day study period, the trend of Ag-RDT test positive rates paralleled that of the epidemic curve. The correlation between the Ag-RDT positive rate and the number of cases (Pearson correlation coefficient: 0.968) is comparable to that of the RT-PCR positive rate (Pearson correlation coefficient: 0.964). The Ag-RDT positive rate exhibited a more advanced leading trend, with Ag-RDT leading by 3 days in comparison to the 2-day lead for RT-PCR. ConclusionThe positive rate of SARS-CoV-2 Ag-RDT tests at community testing stations serves as a good surrogate for assessing virus activity within the community and a useful tool for real-time COVID-19 surveillance. It is a robust indicator of the outbreak trend and near-term numbers of cases. This finding may facilitate the management of subsequent outbreaks of emerging infectious diseases.

Outlining a ‘Semantic Anthropology of Data Science’

Abstract This work intends to describe the humanitarian response to the cholera epidemic carried out by the international health non-governmental organisation Doctors with Africa CUAMM in the provinces of Zambezia, Sofala and Tete in Mozambique. The knowledge and practices of applied medical anthropology have proved to be fundamental in the management of prevention and monitoring activities in homes where cases of cholera have been identified and confirmed. The collection and management of data relating to the epidemiological curve has represented a challenge in the field and pose considerable theoretical problems with respect to the representation, public discourse and policies of local government and large international donors in response to health emergencies caused by the ecological crisis-climate, especially in Africa and Mozambique.