Determination of cut-off and correlates of delay in treatment-seeking of febrile illness: a retrospective analysis

The Malaria Burden: A South African Perspective

Malaria is a deadly disease caused by protozoan pathogens of the Plasmodium parasite. Transmission to humans occurs through the bite of an infected female Anopheles mosquito. According to the World Health Organization (WHO), an estimated 247 million cases of malaria were recorded worldwide in 2021, with approximately 619 000 malaria deaths. The initial signs of malaria can be mild and challenging to diagnose due to the signs and symptoms being similar to those of other illnesses. The malaria burden remains largely concentrated in the WHO sub-Saharan African region and has been recognised as a significant contributor to morbidity and mortality. This review aims to contribute to the existing knowledge on malaria in South Africa, a region within sub-Saharan Africa, focusing on the epidemiology and life cycle of the malaria parasite as well as diagnostic approaches for detecting malaria. In addition, nonpharmacological and pharmacological interventions for treating and preventing malaria infections will also be discussed herein. While there has been a significant reduction in the global burden of this disease, malaria remains a public health issue in South Africa. As such, the implementation of effective preventative measures and strategies, early diagnosis, and appropriate treatment regimens are crucial to reducing the malaria burden in South Africa.

Treatment-seeking behaviours of malaria patients versus non-malaria febrile patients along China-Myanmar border

BACKGROUND

Appropriate malaria treatment-seeking behaviour (TSB) is critical for timely detecting malaria, prompt treatment, and prevention of onward transmission of the disease in a community. This study aimed to compare treatment-seeking behaviours between malaria patients and non-malaria febrile patients, and to analyse the factors associated with appropriate TSB along the China-Myanmar border.

METHODS

A cross-sectional study was carried out to investigate the appropriate TSB of microscopy-confirmed malaria patients versus non-malaria febrile (NMF) patients. An unconditional logistic regression analysis (LRA) was used to identify factors associated with appropriate TSB.

RESULTS

Among 223 malaria patients and 446 NMF patients, 129 (57.8%) of the malaria patients versus 163 (36.5%) of the NMF patients firstly sought treatment in health facilities without laboratory testing for malaria (P < 0.0001). A total of 85(38.1%) of the malaria patients versus 278 (62.3%) of the NMF patients had appropriate TSB, namely, seeking treatment in health facilities with laboratory testing for malaria within 48 h (P < 0.0001). Multivariate LRA identified that the malaria patients with Chinese nationality had less appropriate TSB compared to those with other nationalities (adjusted odds ratio [AOR]: 0.21, 95% confidence interval CI 0.07-0.68, P = 0.0097), and malaria patients residing in urban areas had more appropriate TSB compared to those living in rural areas (AOR: 2.16, 95%CI 1.06-4.39, P = 0.0337).

CONCLUSIONS

TSB was not appropriate in malaria patients. Chinese citizenship and rural residence were two independent factors associated with inappropriate malaria TSB. It is urgently necessary to improve appropriate malaria TSB through effective campaigns of information, education, and communication for malaria control in Myanmar and preventing reestablishment of malaria transmission in Yunnan, China.

Exploring the spatial variation and associated factors of childhood febrile illness among under-five children in Ethiopia: Geographically weighted regression analysis

BACKGROUND

The global burden of febrile illness and the contribution of many fever inducing pathogens have been difficult to quantify and characterize. However, in sub-Saharan Africa it is clear that febrile illness is a common cause of hospital admission, illness and death including in Ethiopia. Therefore the major aim of this study is to explore the spatial variation and associated factors of childhood febrile illness among under-five children in Ethiopia.

METHODS

This study were based on the 2016 Ethiopian Demographic health survey data. A total weighted sample of 10,127 under- five children was included. Data management was done using Stata version-14, Arc-GIS version-10.8 and SatsScan version- 9.6 statistical software. Multi-level log binomial model was fitted to identify factors associated with childhood febrile illness. Variables with a p-value < 0.2 in the bi-variable analysis were considered for the multivariable analysis. In the multivariable multilevel log binomial regression analysis p-value< 0.05, the APR with the 95% CI was reported. Global spatial autocorrelation was done to assess the spatial pattern of childhood febrile illness. Spatial regression was done to identify factors associated with the spatial variations of childhood febrile illness and model comparison was based on adjusted R2 and AICc.

RESULT

The prevalence of febrile illness among under-five children was 13.6% (95% CI: 12.6%, 14 .7%) with significant spatial variation across regions of Ethiopia with Moran's I value of 0.148. The significant hotspot areas of childhood febrile illness were identified in the Tigray, Southeast of Amhara, and North SNPPR. In the GWR analysis, the proportion of PNC, children who had diarrhea, ARI, being 1st birth order, were significant explanatory variables. In the multilevel log binomial regression age of children 7-24 months(APR = 1.33, 95% CI: (1.03, 1.72)), maternal age 30-39 years (APR = 1.36 95% CI: 1.02, 1.80)), number of children (APR = 1.78, 95% CI: 0.96, 3.3), diarrhea(APR = 5.3% 95% CI: (4.09, 6.06)), ARI (APR = 11.5, 95% CI: (9.2, 14.2)) and stunting(APR = 1.21; 95% CI: (0.98, 1.49) were significantly associated with childhood febrile illness.

CONCLUSION

Childhood febrile illness remains public health problem in Ethiopia. On spatial regression analysis proportion of women who had PNC, proportion of children who had diarrhea, proportion of children who had ARI, and proportion of children who had being 1st birth order were associated factors. The detailed map of childhood febrile illness and its predictors could assist health program planners and policy makers to design targeted public health interventions for febrile illness.

Malaria treatment-seeking behaviour and its associated factors: A cross-sectional study in rural East Nusa Tenggara Province, Indonesia

INTRODUCTION

The World Health Organization recommends seeking medical treatment within 24 hours after transmission of malaria to reduce the risk of severe complications and its onwards spread. However, in some parts of Indonesia, including East Nusa Tenggara Province (ENTP), this adherence is not achieved for a range of reasons including delays in visiting health centres. This study aims to determine factors related to the poor understanding of appropriate malaria treatment-seeking behaviour (AMTSB) of rural adults in ENTP. AMTSB was defined as seeking treatment at professional health facilities within 24 hours of the onset of malaria symptoms.

METHODS

A cross-sectional study was conducted in the East Sumba, Belu, and East Manggarai district of ENTP between October and December 2019. A multi-stage cluster sampling procedure was applied to enrol 1503 participants aged between 18 and 89 years of age. Data were collected through face-to-face interviews. Multivariable logistic regression analyses were used to assess significant factors associated with the poor understanding of AMTSB.

RESULTS

Eighty-six percent of participants were found to be familiar with the term malaria. However, poor understanding level of AMTSB in rural adults of ENTP achieved 60.4% with a 95% confidence interval (CI): 56.9-63.8. Poor understanding of AMTSB was significantly higher for adults with no education (adjusted odds ratio (AOR) 3.42, 95% CI: 1.81, 6.48) compared to those with a diploma or above education level; having low SES (AOR: 1.87, 95% CI: 1.19, 2.96) compared to those having high SES; residing at least three kilometres (km) away from the nearest health facilities (AOR: 1.73, 95% CI: 1.2, 2.5) compared to those living within one km from the nearest health service; and working as farmer (AOR: 1.63, 95% CI: 1.01-2.63) compared to those working at government or non-government sector. Whilst, other factors such as ethnicity and family size were not associated with the poor understanding of AMTSB.

CONCLUSION

The proportion of rural adults having a poor understanding of AMTSB was high leading to ineffective implementation of artemisinin-based combination therapies as the method to treat malaria in ENTP. Improving awareness of AMTSB for rural adults having low level education, low SES, working as a farmer, and living at least three km from the nearest health facilities is critical to support the efficacy of malaria treatment in ENTP. This method will support the Indonesian government's objective to achieve malaria elimination by 2030.

Healthcare Utilization Survey in the Hybrid Model of the Surveillance for Enteric Fever in India (SEFI) Study: Processes, Monitoring, Results, and Challenges

Background

Lack of reliable data in India drove the “Surveillance of Enteric Fever in India” (SEFI) concept. Hybrid surveillance, combining facility-based surveillance for the crude incidence, and a community-based healthcare utilization survey (HCUS) to calculate the factor needed to arrive at the adjusted incidence, was used in 6 sites. The HCUS aimed to determine the percentage of utilization of study facilities by the catchment population for hospitalizations due to febrile illness.

Methods

Population proportional to size sampling and systematic random sampling, in 2 stages, were used to survey 5000 households per site. Healthcare utilization was assessed.

Results

Febrile illness accounted for 20% of admissions among 137 990 individuals from 30 308 households. Only 9.6%–38.3% of those admitted with febrile illness sought care in the study hospitals. The rate of rural utilization of the private sector for hospitalization was 67.6%. The rate of hospitalization for febrile illness, per 1000 population, ranged from 2.6 in Manali to 9.6 in Anantapur; for 25.8% of the deaths associated with febrile illness, no facility was used before death.

Conclusions

One in 5 hospitalizations were associated with fever. Rural utilization of the private sector for hospitalization due to febrile illness was more than that of the public sector. Healthcare utilization patterns for hospital admissions due to febrile illness varied across sites. A meticulously performed HCUS is pivotal for accurate incidence estimation in a hybrid surveillance.

Clinical Trials Registration

ISRCTN72938224.