Geographical coverage of SARS-CoV-2 screening and care centers in Haiti: what do national surveillance data tell us?

BACKGROUND: In Haiti, reported incidence and mortality rates for COVID-19 were lower than expected. We aimed to analyze factors at communal and individual level that might lead to an underestimation of the true burden of the COVID-19 epidemic in Haiti during its first two years. METHODS: We analyzed national COVID-19 surveillance data from March 2020 to December 2021, to describe the epidemic using cluster detection, time series, and cartographic approach. We performed multivariate Quasi-Poisson regression models to determine socioeconomic factors associated with incidence and mortality. We performed a mixed-effect logistic regression model to determine individual factors associated with the infection. RESULTS: Among the 140 communes of Haiti, 57 (40.7%) had a COVID-19 screening center, and the incidence was six times higher in these than in those without. Only 22 (15.7%) communes had a COVID-19 care center, and the mortality was five times higher in these than in those without. All the richest communes had a COVID-19 screening center while only 30.8% of the poorest had one. And 75% of the richest communes had a COVID-19 care center while only 15.4% of the poorest had one. Having more than three healthcare workers per 1000 population in the commune was positively associated with the incidence (SIR: 3.31; IC95%: 2.50, 3.93) and the mortality (SMR: 2.73; IC95%: 2.03, 3.66). At the individual level, male gender (adjusted OR: 1.11; IC95%: 1.01, 1.22), age with a progressive increase of the risk compared to youngers, and having Haitian nationality only (adjusted OR:2.07; IC95%: 1.53, 2.82) were associated with the infection. CONCLUSIONS: This study highlights the weakness of SARS-CoV-2 screening and care system in Haiti, particularly in the poorest communes, suggesting that the number of COVID-19 cases and deaths were probably greatly underestimated.

Geo-epidemiology of animal tuberculosis and Mycobacterium bovis genotypes in livestock in a small, high-incidence area in Sicily, Italy.

Introduction: The persistence of animal tuberculosis (TB) in livestock is a major concern in Sicily, Italy. The objective of this study was to elucidate the transmission dynamics of M. bovis infection in a highly circumscribed, and at the same time geographically diverse, high-risk area of the island through an in-depth geo-epidemiological investigation of TB in cattle and black pigs raised in small-scale extensive farms across the district of Caronia. Methods: We used genotype analysis coupled with geographic information system (GIS) technology and phylogenetic inference to characterize the spatial distribution of TB and M. bovis genotypes in livestock and the genetic relationships between M. bovis isolates. A total of 589 M. bovis isolates collected from slaughtered cattle (n = 527) and Sicilian black pigs (n = 62) over a 5-year period (2014-2018) were included in the study. Results: TB was widespread throughout the district and was most frequent in the north-central area of the district, especially along one of the district's streams. We identified a total of 62 M. bovis genotypes. Identical genetic profiles were isolated from both neighboring and non-neighburing herds. The 10 most frequent genotypes, accounting for 82% of M. bovis isolates, showed geographic specificities in that they tended to cluster in specific spatial niches. The landscape structure of these niches-i.e. steep slopes, rocky ridges, meadows and streams-is likely to have had a significant influence on the distribution of TB among livestock in Caronia. Higher concentrations of TB were observed along streams and in open meadows, while rocky ridges and slopes appeared to have hampered the spread of TB. Discussion: The geographical distribution of TB cases among livestock in Caronia is consistent with several epidemiological scenarios (e.g., high density of infected herds along the streams or in hilly plateau where livestock share pastures). Landscape structure is likely to play an important role in the transmission and persistence of M. bovis infection across the district. Additional potential risk factors, such as livestock trading and extensive breeding methods, are also discussed. Our results will contribute to the improvement of surveillance, control and eradication activities of TB in Sicily by the implementation of ad hoc TB control measures, especially in farms located along streams, sharing common pastures or with mixed animal species.

Geo-epidemiological approach of the COVID-19 pandemic in France and in Europe for public health policies.

The spread of the COVID-19 pandemic has shown great heterogeneity between countries that merits investigation. There is a need to better highlight the variability in the pandemic trajectories in different geographic areas. By using openly available data from 'GitHub' COVID-19 dataset for Europe and from the official dataset of France for the period 2020 to 2021, I present the three COVID-19 waves in France and Europe in maps. The epidemic trends across areas display different evolutions for different time periods. National and European public health authorities will be able to improve allocation of resources for more effective public health measures based on geo-epidemiological analyses.

Heterogeneity of the COVID-19 Pandemic in the United States of America: A Geo-Epidemiological Perspective.

The spread of the COVID-19 pandemic has shown great heterogeneity between regions of countries, e. g., in the United States of America (USA). With the growing of the worldwide COVID-19 pandemic, there is a need to better highlight the variability in the trajectory of this disease in different worldwide geographic areas. Indeed, the epidemic trends across areas can display completely different evolution at a given time. Geo-epidemiological analyses using data, that are publicly available, could be a major topic to help governments and public administrations to implement health policies. Geo-epidemiological analyses could provide a basis for the implementation of relevant public health policies. With the COVID-19 pandemic, geo-epidemiological analyses can be readily utilized by policy interventions and USA public health authorities to highlight geographic areas of particular concern and enhance the allocation of resources.

Urban landscape and infection risk in free-roaming cats.

Despite public concern on the role of free-roaming cats as reservoirs of zoonotic agents, little is known about the influence of urban and peri-urban landscapes on the exposure risk. We evaluated the seroprevalence of three zoonotic agents (Chlamydia felis, Coxiella burnetii and Toxoplasma gondii) in domestic cats (Felis catus). Two hundred and ninety-one free-roaming cats were trapped in Murcia municipality (Southeast Spain), and their sera were tested for specific antibodies against T. gondii using a modified agglutination test (MAT), and for C. felis, C. burnetii and feline immunodeficiency virus (FIV) antibodies with ELISA technique. Pathogen seroprevalence at 95% CI was calculated for each sex and age category (up to and over 12 months) and compared with a chi-squared test. The role of human population density and urban landscape characteristics on the risk of pathogen exposure in the cat population was explored using generalized linear models. Seropositivity against a single pathogen was found in 60% of the cats, while 19% was seropositive for two or three pathogens. Seroprevalence of C. felis was 8% (CI95% : 5-11), 37% (CI95% : 31-42) for C. burnetii and 42% (CI95% : 36-47) for T. gondii. In addition to these three pathogens, FIV seropositivity was low (1%, CI95% : -0.1 to 2) and adult cats were more likely to be seropositive to C. burnetii than young individuals (OR: 2.3, CI95% : 1.2-4.2). No sex or age class differences in seroprevalence were observed for the rest of the pathogens. Seropositivity was correlated with water surface areas for C. felis, and not with crop areas. Coxiella burnetii seropositivity was correlated with the percentage of urban areas (continuous with only buildings and discontinuous, that include buildings, parks, and pedestrian and urban green areas), human population size and peri-urban areas with shrubs, and not correlated with other agricultural landscapes (orchards and crop areas). However, the seroprevalence of T. gondii was only associated with agricultural landscapes such as orchards. The detection of hotspot areas of high pathogen exposure risk is the basis for municipal services to implement surveillance and risk factor control campaigns in specific-risk areas, including (a) efficient health management of urban cat colonies by geographical location, population census and health status monitoring of the components of each cat colony, (b) improvement of hygiene and sanitary conditions at the feeding points of the cat colony and (c) free-roaming cat trapping for health monitoring and, in the long term, to know the evolution of the health status of their populations.

Test positivity - Evaluation of a new metric to assess epidemic dispersal mediated by non-symptomatic cases.

Epidemic control may be hampered when the percentage of asymptomatic cases is high. Seeking remedies for this problem, test positivity was explored between the first 60 to 90 epidemic days in six countries that reported their first COVID-19 case between February and March 2020: Argentina, Bolivia, Chile, Cuba, Mexico, and Uruguay. Test positivity (TP) is the percentage of test-positive individuals reported on a given day out of all individuals tested the same day. To generate both country-specific and multi-country information, this study was implemented in two stages. First, the epidemiologic data of the country infected last (Uruguay) were analyzed. If at least one TP-related analysis yielded a statistically significant relationship, later assessments would investigate the six countries. The Uruguayan data indicated (i) a positive correlation between daily TP and daily new cases (r = 0.75); (ii) a negative correlation between TP and the number of tests conducted per million inhabitants (TPMI, r = -0.66); and (iii) three temporal stages, which differed from one another in both TP and TPMI medians (p < 0.01) and, together, revealed a negative relationship between TPMI and TP. No significant relationship was found between TP and the number of active or recovered patients. The six countries showed a positive correlation between TP and the number of deaths/million inhabitants (DMI, r = 0.65, p < 0.01). With one exception -a country where isolation was not pursued-, all countries showed a negative correlation between TP and TPMI (r = 0.74). The temporal analysis of country-specific policies revealed four patterns, characterized by: (1) low TPMI and high DMI, (2) high TPMI and low DMI; (3) an intermediate pattern, and (4) high TPMI and high DMI. Findings support the hypothesis that test positivity may guide epidemiologic policy-making, provided that policy-related factors are considered and high-resolution geographical data are utilized.

Geo-epidemiology and environmental co-variate mapping of primary biliary cholangitis and primary sclerosing cholangitis.

BACKGROUND & AIMS: Autoimmune liver disease (AILD) is thought to result from a complex interplay between genetics and the environment. Studies to date have focussed on primary biliary cholangitis (PBC) and demonstrated higher disease prevalence in more urban, polluted, and socially deprived areas. This study utilises a large cohort of patients with PBC and primary sclerosing cholangitis (PSC) to investigate potential environmental contributors to disease and to explore whether the geo-epidemiology of PBC and PSC are disease-specific or pertain to cholestatic AILD in general. METHODS: All adult patients with PBC and PSC in a tightly defined geographical area within the UK were identified. Point- and area-based analyses and structural equation modelling (SEM) were used to investigate for disease clustering and examine for relationships between prevalence, distribution of environmental contaminants, and socio-economic status. RESULTS: We identified 2,150 patients with PBC and 472 with PSC. Significant spatial clustering was seen for each disease. A high prevalence of PBC was found in urban, post-industrial areas with a strong coal-mining heritage and increased environmental cadmium levels, whereas a high PSC prevalence was found in rural areas and inversely associated with social deprivation. CONCLUSIONS: This study demonstrates spatial clustering of PBC and PSC and adds to our understanding of potential environmental co-variates for both diseases. Disease clustering, within the same geographical area but over different scales, is confirmed for each disease with distinct risk profiles identified and associations with separate putative environmental factors and socio-economic status. This suggests that different triggers and alternative pathways determine phenotypic expression of autoimmunity in the affected population. Co-variate analysis points towards the existence of specific disease triggers. LAY SUMMARY: This study looked for potential environmental triggers in patients with primary biliary cholangitis (PBC) and primary sclerosing cholangitis (PSC) living in the north-east of England and north Cumbria. We found that PBC was more common in urban areas with a history of coal mining and high levels of cadmium whereas PSC was more common in rural areas with lower levels of social deprivation.

Spatio-Temporal Dynamic of Malaria Incidence: A Comparison of Two Ecological Zones in Mali.

Malaria transmission largely depends on environmental, climatic, and hydrological conditions. In Mali, malaria epidemiological patterns are nested within three ecological zones. This study aimed at assessing the relationship between those conditions and the incidence of malaria in Dangassa and Koila, Mali. Malaria data was collected through passive case detection at community health facilities of each study site from June 2015 to January 2017. Climate and environmental data were obtained over the same time period from the Goddard Earth Sciences (Giovanni) platform and hydrological data from Mali hydraulic services. A generalized additive model was used to determine the lagged time between each principal component analysis derived component and the incidence of malaria cases, and also used to analyze the relationship between malaria and the lagged components in a multivariate approach. Malaria transmission patterns were bimodal at both sites, but peak and lull periods were longer lasting for Koila study site. Temperatures were associated with malaria incidence in both sites. In Dangassa, the wind speed (p = 0.005) and river heights (p = 0.010) contributed to increasing malaria incidence, in contrast to Koila, where it was humidity (p < 0.001) and vegetation (p = 0.004). The relationships between environmental factors and malaria incidence differed between the two settings, implying different malaria dynamics and adjustments in the conception and plan of interventions.

How to Estimate Optimal Malaria Readiness Indicators at Health-District Level: Findings from the Burkina Faso Service Availability and Readiness Assessment (SARA) Data.

One of the major contributors of malaria-related deaths in Sub-Saharan African countries is the limited accessibility to quality care. In these countries, malaria control activities are implemented at the health-district level (operational entity of the national health system), while malaria readiness indicators are regionally representative. This study provides an approach for estimating health district-level malaria readiness indicators from survey data designed to provide regionally representative estimates. A binomial-hierarchical Bayesian spatial prediction method was applied to Burkina Faso Service Availability and Readiness Assessment (SARA) survey data to provide estimates of essential equipment availability and readiness for malaria care. Predicted values of each indicator were adjusted by the type of health facility, location, and population density. Then, a health district composite readiness profile was built via hierarchical ascendant classification. All surveyed health-facilities were mandated by the Ministry of Health to manage malaria cases. The spatial distribution of essential equipment and malaria readiness was heterogeneous. Around 62.9% of health districts had a high level of readiness to provide malaria care and prevention during pregnancy. Low-performance scores for managing malaria cases were found in big cities. Health districts with low coverage for both first-line antimalarial drugs and rapid diagnostic tests were Baskuy, Bogodogo, Boulmiougou, Nongr-Massoum, Sig-Nonghin, Dafra, and Do. We provide health district estimates and reveal gaps in basic equipment and malaria management resources in some districts that need to be filled. By providing local-scale estimates, this approach could be replicated for other types of indicators to inform decision makers and health program managers and to identify priority areas.

Geo-Epidemiology of Malaria at the Health Area Level, Dire Health District, Mali, 2013-2017.

Background: According to the World Health Organization, there were more than 228 million cases of malaria globally in 2018, with 93% of cases occurring in Africa; in Mali, a 13% increase in the number of cases was observed between 2015 and 2018; this study aimed to evaluate the impact of meteorological and environmental factors on the geo-epidemiology of malaria in the health district of Dire, Mali. Methods: Meteorological and environmental variables were synthesized using principal component analysis and multiple correspondence analysis, the relationship between malaria incidence and synthetic indicators was determined using a multivariate general additive model; hotspots were detected by SaTScan. Results: Malaria incidence showed high inter and intra-annual variability; the period of high transmission lasted from September to February; health areas characterized by proximity to the river, propensity for flooding and high agricultural yield were the most at risk, with an incidence rate ratio of 2.21 with confidence intervals (95% CI: 1.85-2.58); malaria incidence in Dire declined from 120 to 20 cases per 10,000 person-weeks between 2013 and 2017. Conclusion: The identification of areas and periods of high transmission can help improve malaria control strategies.

Where and when to vaccinate? Interdisciplinary design and evaluation of the 2018 Tanzanian anti-rabies campaign.

OBJECTIVES: Hoping to improve health-related effectiveness, a two-phase vaccination against rabies was designed and executed in northern Tanzania in 2018, which included geo-epidemiological and economic perspectives. METHODS: Considering the local bio-geography and attempting to rapidly establish a protective ring around a city at risk, the first phase intervened on sites surrounding that city, where the population density was lower than in the city at risk. The second phase vaccinated a rural area. RESULTS: No rabies-related case has been reported in the vaccinated areas for over a year post-immunisation; hence, the campaign is viewed as highly cost-effective. Other metrics included: rapid implementation (concluded in half the time spent on other campaigns) and the estimated cost per protected life, which was 3.28 times lower than in similar vaccinations. CONCLUSIONS: The adopted design emphasised local bio-geographical dynamics: it prevented the occurrence of an epidemic in a city with a higher demographic density than its surrounding area and it also achieved greater effectiveness than average interventions. These interdisciplinary, policy-oriented experiences have broad and immediate applications in settings of limited and/or time-sensitive (expertise, personnel, and time available to intervene) resources and conditions.

Geographic integration of hepatitis C virus: A global threat.

AIM: To assess hepatitis C virus (HCV) geographic integration, evaluate the spatial and temporal evolution of HCV worldwide and propose how to diminish its burden. METHODS: A literature search of published articles was performed using PubMed, MEDLINE and other related databases up to December 2015. A critical data assessment and analysis regarding the epidemiological integration of HCV was carried out using the meta-analysis method. RESULTS: The data indicated that HCV has been integrated immensely over time and through various geographical regions worldwide. The history of HCV goes back to 1535 but between 1935 and 1965 it exhibited a rapid, exponential spread. This integration is clearly seen in the geo-epidemiology and phylogeography of HCV. HCV integration can be mirrored either as intra-continental or trans-continental. Migration, drug trafficking and HCV co-infection, together with other potential risk factors, have acted as a vehicle for this integration. Evidence shows that the geographic integration of HCV has been important in the global and regional distribution of HCV. CONCLUSION: HCV geographic integration is clearly evident and this should be reflected in the prevention and treatment of this ongoing pandemic.