Estimating the spatial distribution of acute undifferentiated fever (AUF) and associated risk factors using emergency call data in India. A symptom-based approach for public health surveillance

Review on Scrub Typhus: An Important Etiology of Acute Undifferentiated Fever Illness

One of India's predominant public health issues is acute undifferentiated fever illness (AUFI), a typical response to an infectious agent. Diagnosis becomes challenging when the disease has been reported with fever as the primary symptom. Among the cases presenting at a tertiary care hospital in central India, 88% had an acute undifferentiated fever, the most common being dengue infection. In India, rural communities are at more risk from AUFI than cities. Most of those in danger are those who reside in remote areas, and one of the most significant risks is for those who reside close to forests. AUFI is a complex condition for physicians to deal with and is one of the most frequent clinical conditions for which empirical treatment is required. Nowadays, AUFI can be managed by a syndromic approach with the judicial use of antibiotics. Symptoms of AUFI, along with myalgia, headache, and anorexia, can be caused by various illnesses. Patients are recommended to undertake a battery of investigations, which may delay the therapy and increase expenses because many diseases may present with the same symptoms. In the developed world, viral illness is the primary cause of AUFI. However, in developing countries like India, it can also be brought on by potentially curable but life-threatening conditions such as malaria, leptospirosis, hantavirus infection, and Japanese encephalitis. Lack of knowledge of the locally prevalent illnesses, which might be the cause of AUFI, and lack of preliminary screening and diagnostics at the point of care to identify the etiologies make it difficult to control these generally curable causes of the burden of AUFI, especially in tropical and subtropical countries. A deeper understanding of AUFI is required to develop better diagnostics and cures for various etiologies, especially scrub typhus.

Defining symptoms of malaria in India in an era of asymptomatic infections

Background

Malaria is a major public health problem in India. Data from surveys totaling 3031 participants at three sites revealed a high proportion of asymptomatic infections, complicating diagnosis. The aim of this study was to identify differences in complaints and symptoms between sites, and factors associated with asymptomatic Plasmodium infections.

Methods

Published data from community-based cross-sectional studies conducted between 2012 and 2015 in Nadiad (Gujarat), Chennai (Tamil Nadu), and Rourkela (Odisha) as part of the Center for the Study of Complex Malaria in India were analysed. Complaints and symptoms were systematically recorded, and Plasmodium infections confirmed using microscopy, rapid diagnostic tests (RDTs), and polymerase chain reaction (PCR). Multivariate analyses were conducted to determine the association between general symptoms and age, season, or gender, and factors associated with asymptomatic Plasmodium infections were assessed.

Results

Complaints of any illness were lowest in Chennai (17.7%), 30.6% in Rourkela and 42.7% in Nadiad. Complaints were more often reported for children; gender differences were noted in Rourkela only. In Nadiad, 7.0% of 796 participants were positive for malaria by PCR (32% Plasmodium falciparum); 78.6% had a history of fever or documented fever, 14.3% had other symptoms, and 7.1% were “truly asymptomatic”. For Chennai this was 29.2%, 4.2% and 66.7% respectively, with a malaria prevalence of 2.6% by PCR of 928 participants (29% P. falciparum). In Rourkela, with 7.7% of 1307 participants positive for malaria by PCR (82% P. falciparum), the percentages were 35.6%, 24.8% and 39.6%, respectively. In Rourkela, asymptomatic infections were associated with young age and male gender (microscopy or RDT), and with rainy season (PCR). In the same site, participants with Plasmodium vivax were more likely to be asymptomatic (11/18 or 61.1%) than persons with P. falciparum mono-infections (27/78 or 34.6%); gametocytes for P. falciparum were evenly distributed between symptomatic and asymptomatic infections (2/53 vs. 2/49, respectively). The addition of the symptoms “headache”, “aches” and “chills” to fever improved the case-definition of symptomatic malaria.

Conclusion

There were considerable differences in complaints at the three sites in India. Malaria and asymptomatic infections differ by region, indicating that malaria elimination will require localized approaches.

A new approach to spatial identification of potential health hazards associated with childhood asthma

RESEARCH BACKGROUND

Childhood asthma is a chronic disease, known to be linked to prolonged exposure to air pollution. However, the identification of specific health hazards, associated with childhood asthma is not always straightforward, due to the presence of multiple sources of air pollution in urban areas. In this study, we test a novel approach to the spatial identification of environmental hazards that have the highest probability of association with the observed asthma morbidity patterns.

METHODS

The effect of a particular health hazard on population morbidity is expected to weaken with distance. To account for this effect, we rank potential health hazards based on the strength of association between the observed morbidity patterns and wind-direction weighted proximities to these locations. We validate this approach by applying it to a study of spatial patterns of childhood asthma in the Greater Haifa Metropolitan Area (GHMA) in Israel, characterised by multiple health hazards.

RESULTS

We identified a spot in the local industrial zone as the primary risk source for the observed asthma morbidity patterns. Multivariate regressions, controlling for socio-economic and geographic variables, revealed that the observed incidence rates of asthma tend to decline as a function of distance from the identified industrial location.

CONCLUSION

The proposed identification approach uses disease patterns as its main input, and can be used by researches as a preliminary risk assessment tool, in cases in which specific sources of locally elevated morbidity are unclear or cannot be identified by traditional methods.

Is the current pertussis incidence only the results of testing? A spatial and space-time analysis of pertussis surveillance data using cluster detection methods and geographically weighted regression modelling

BACKGROUND

Despite high vaccination coverage, pertussis incidence in the Netherlands is amongst the highest in Europe with a shifting tendency towards adults and elderly. Early detection of outbreaks and preventive actions are necessary to prevent severe complications in infants. Efficient pertussis control requires additional background knowledge about the determinants of testing and possible determinants of the current pertussis incidence. Therefore, the aim of our study is to examine the possibility of locating possible pertussis outbreaks using space-time cluster detection and to examine the determinants of pertussis testing and incidence using geographically weighted regression models.

METHODS

We analysed laboratory registry data including all geocoded pertussis tests in the southern area of the Netherlands between 2007 and 2013. Socio-demographic and infrastructure-related population data were matched to the geo-coded laboratory data. The spatial scan statistic was applied to detect spatial and space-time clusters of testing, incidence and test-positivity. Geographically weighted Poisson regression (GWPR) models were then constructed to model the associations between the age-specific rates of testing and incidence and possible population-based determinants.

RESULTS

Space-time clusters for pertussis incidence overlapped with space-time clusters for testing, reflecting a strong relationship between testing and incidence, irrespective of the examined age group. Testing for pertussis itself was overall associated with lower socio-economic status, multi-person-households, proximity to primary school and availability of healthcare. The current incidence in contradiction is mainly determined by testing and is not associated with a lower socioeconomic status.

DISCUSSION

Testing for pertussis follows to an extent the general healthcare seeking behaviour for common respiratory infections, whereas the current pertussis incidence is largely the result of testing. More testing would thus not necessarily improve pertussis control. Detecting outbreaks using space-time cluster detection is feasible but needs to adjust for the strong impact of testing on the detection of pertussis cases.

The Spatial Distribution of Hepatitis C Virus Infections and Associated Determinants--An Application of a Geographically Weighted Poisson Regression for Evidence-Based Screening Interventions in Hotspots

Background

Hepatitis C Virus (HCV) infections are a major cause for liver diseases. A large proportion of these infections remain hidden to care due to its mostly asymptomatic nature. Population-based screening and screening targeted on behavioural risk groups had not proven to be effective in revealing these hidden infections. Therefore, more practically applicable approaches to target screenings are necessary. Geographic Information Systems (GIS) and spatial epidemiological methods may provide a more feasible basis for screening interventions through the identification of hotspots as well as demographic and socio-economic determinants.

Methods

Analysed data included all HCV tests (n = 23,800) performed in the southern area of the Netherlands between 2002–2008. HCV positivity was defined as a positive immunoblot or polymerase chain reaction test. Population data were matched to the geocoded HCV test data. The spatial scan statistic was applied to detect areas with elevated HCV risk. We applied global regression models to determine associations between population-based determinants and HCV risk. Geographically weighted Poisson regression models were then constructed to determine local differences of the association between HCV risk and population-based determinants.

Results

HCV prevalence varied geographically and clustered in urban areas. The main population at risk were middle-aged males, non-western immigrants and divorced persons. Socio-economic determinants consisted of one-person households, persons with low income and mean property value. However, the association between HCV risk and demographic as well as socio-economic determinants displayed strong regional and intra-urban differences.

Discussion

The detection of local hotspots in our study may serve as a basis for prioritization of areas for future targeted interventions. Demographic and socio-economic determinants associated with HCV risk show regional differences underlining that a one-size-fits-all approach even within small geographic areas may not be appropriate. Future screening interventions need to consider the spatially varying association between HCV risk and associated demographic and socio-economic determinants.