The interplay of movement and spatiotemporal variation in transmission degrades pandemic control.

Successful public health regimes for COVID-19 push below unity long-term regional Rt -the average number of secondary cases caused by an infectious individual. We use a susceptible-infectious-recovered (SIR) model for two coupled populations to make the conceptual point that asynchronous, variable local control, together with movement between populations, elevates long-term regional Rt , and cumulative cases, and may even prevent disease eradication that is otherwise possible. For effective pandemic mitigation strategies, it is critical that models encompass both spatiotemporal heterogeneity in transmission and movement.

Disparities in influenza mortality and transmission related to sociodemographic factors within Chicago in the pandemic of 1918.

Social factors have been shown to create differential burden of influenza across different geographic areas. We explored the relationship between potential aggregate-level social determinants and mortality during the 1918 influenza pandemic in Chicago using a historical dataset of 7,971 influenza and pneumonia deaths. Census tract-level social factors, including rates of illiteracy, homeownership, population, and unemployment, were assessed as predictors of pandemic mortality in Chicago. Poisson models fit with generalized estimating equations (GEEs) were used to estimate the association between social factors and the risk of influenza and pneumonia mortality. The Poisson model showed that influenza and pneumonia mortality increased, on average, by 32.2% for every 10% increase in illiteracy rate adjusted for population density, homeownership, unemployment, and age. We also found a significant association between transmissibility and population density, illiteracy, and unemployment but not homeownership. Lastly, analysis of the point locations of reported influenza and pneumonia deaths revealed fine-scale spatiotemporal clustering. This study shows that living in census tracts with higher illiteracy rates increased the risk of influenza and pneumonia mortality during the 1918 influenza pandemic in Chicago. Our observation that disparities in structural determinants of neighborhood-level health lead to disparities in influenza incidence in this pandemic suggests that disparities and their determinants should remain targets of research and control in future pandemics.

High burden of malaria following scale-up of control interventions in Nchelenge District, Luapula Province, Zambia.

BACKGROUND: Malaria control interventions have been scaled-up in Zambia in conjunction with a malaria surveillance system. Although substantial progress has been achieved in reducing morbidity and mortality, national and local information demonstrated marked heterogeneity in the impact of malaria control across the country. This study reports the high burden of malaria in Nchelenge District, Luapula Province, Zambia from 2006 to 2012 after seven years of control measures. METHODS: Yearly aggregated information on cases of malaria, malaria deaths, use of malaria diagnostics, and malaria control interventions from 2006 to 2012 were obtained from the Nchelenge District Health Office. Trends in the number of malaria cases, methods of diagnosis, malaria positivity rate among pregnant women, and intervention coverage were analysed using descriptive statistics. RESULTS: Malaria prevalence remained high, increasing from 38% in 2006 to 53% in 2012. Increasing numbers of cases of severe malaria were reported until 2010. Intense seasonal malaria transmission was observed with seasonal declines in the number of cases between April and August, although malaria transmission continued throughout the year. Clinical diagnosis without accompanying confirmation declined from 95% in 2006 to 35% in 2012. Intervention coverage with long-lasting insecticide-treated nets and indoor residual spraying increased from 2006 to 2012. CONCLUSIONS: Despite high coverage with vector control interventions, the burden of malaria in Nchelenge District, Zambia remained high. The high parasite prevalence could accurately reflect the true burden, perhaps in part as a consequence of population movement, or improved access to care and case reporting. Quality information at fine spatial scales will be critical for targeting effective interventions and measurement of progress.

Mobile phones improve case detection and management of malaria in rural Bangladesh.

BACKGROUND: The recent introduction of mobile phones into the rural Bandarban district of Bangladesh provided a resource to improve case detection and treatment of patients with malaria. METHODS: During studies to define the epidemiology of malaria in villages in south-eastern Bangladesh, an area with hypoendemic malaria, the project recorded 986 mobile phone calls from families because of illness suspected to be malaria between June 2010 and June 2012. RESULTS: Based on phone calls, field workers visited the homes with ill persons, and collected blood samples for malaria on 1,046 people. 265 (25%) of the patients tested were positive for malaria. Of the 509 symptomatic malaria cases diagnosed during this study period, 265 (52%) were detected because of an initial mobile phone call. CONCLUSION: Mobile phone technology was found to be an efficient and effective method for rapidly detecting and treating patients with malaria in this remote area. This technology, when combined with local knowledge and field support, may be applicable to other hard-to-reach areas to improve malaria control.

The changing burden of malaria and association with vector control interventions in Zambia using district-level surveillance data, 2006-2011.

BACKGROUND: Malaria control was strengthened in Zambia over the past decade. The two primary interventions for vector control are indoor residual spraying (IRS) and long-lasting insecticide-treated nets (LLINs). Using passive malaria surveillance data collected from 2006 to 2011 through the Zambian District Health Information System, the associations between increased coverage with LLINs and IRS and the burden of malaria in Zambia were evaluated. METHODS: National passive malaria surveillance data from 2006 to 2011 were analysed. A district-level, random-effects model with Poisson regression was used to explore the association between malaria cases and coverage with LLINs and IRS. Malaria cases and LLINs and IRS coverage were mapped to visualize spatiotemporal variation in malaria for each year. RESULTS: From 2006-2011, 24.6 million LLINs were distributed and 6.4 million houses were sprayed with insecticide. Coverage with LLINs was not uniformly distributed over the study period and IRS was targeted to central and southern districts where malaria transmission was low. LLIN coverage was associated with a reduction in malaria cases, although an increase in the number of malaria cases was reported in some districts over the study period. A high burden of malaria persisted in north-eastern Zambia, whereas a reduction in the number of reported malaria cases was observed in western and southern Zambia. CONCLUSION: Enhanced and targeted interventions in north-eastern Zambia where the burden of malaria remains high, as well as efforts to sustain low malaria transmission in the south-west, will be necessary for Zambia to achieve the national goal of being malaria free by 2030.

Forecasting Outbreaks of Hantaviral Disease: Future Directions in Geospatial Modeling.

Hantaviral diseases have been recognized as 'place diseases' from their earliest identification and, epidemiologically, are tied to single host species with transmission occurring from infectious hosts to humans. As such, human populations are most at risk when they are in physical proximity to suitable habitats for reservoir populations, when numbers of infectious hosts are greatest. Because of the lags between improving habitat conditions and increasing infectious host abundance and spillover to humans, it should be possible to anticipate (forecast) where and when outbreaks will most likely occur. Most mammalian hosts are associated with specific habitat requirements, so identifying these habitats and the ecological drivers that impact population growth and the dispersal of viral hosts should be markers of the increased risk for disease outbreaks. These regions could be targeted for public health and medical education. This paper outlines the rationale for forecasting zoonotic outbreaks, and the information that needs to be clarified at various levels of biological organization to make the forecasting of orthohantaviruses successful. Major challenges reflect the transdisciplinary nature of forecasting zoonoses, with needs to better understand the implications of the data collected, how collections are designed, and how chosen methods impact the interpretation of results.

Two Decades of Wildlife Pathogen Surveillance: Case Study of Choclo orthohantavirus and Its Wild Reservoir Oligoryzomys costaricensis.

The Costa Rican pygmy rice rat (Oligoryzomys costaricensis) is the primary reservoir of Choclo orthohantavirus (CHOV), the causal agent of hantavirus disease, pulmonary syndrome, and fever in humans in Panama. Since the emergence of CHOV in early 2000, we have systematically sampled and archived rodents from >150 sites across Panama to establish a baseline understanding of the host and virus, producing a permanent archive of holistic specimens that we are now probing in greater detail. We summarize these collections and explore preliminary habitat/virus associations to guide future wildlife surveillance and public health efforts related to CHOV and other zoonotic pathogens. Host sequences of the mitochondrial cytochrome b gene form a single monophyletic clade in Panama, despite wide distribution across Panama. Seropositive samples were concentrated in the central region of western Panama, consistent with the ecology of this agricultural commensal and the higher incidence of CHOV in humans in that region. Hantavirus seroprevalence in the pygmy rice rat was >15% overall, with the highest prevalence in agricultural areas (21%) and the lowest prevalence in shrublands (11%). Host-pathogen distribution, transmission dynamics, genomic evolution, and habitat affinities can be derived from the preserved samples, which include frozen tissues, and now provide a foundation for expanded investigations of orthohantaviruses in Panama.

Modelling malaria treatment practices in Bangladesh using spatial statistics.

BACKGROUND: Malaria treatment-seeking practices vary worldwide and Bangladesh is no exception. Individuals from 88 villages in Rajasthali were asked about their treatment-seeking practices. A portion of these households preferred malaria treatment from the National Control Programme, but still a large number of households continued to use drug vendors and approximately one fourth of the individuals surveyed relied exclusively on non-control programme treatments. The risks of low-control programme usage include incomplete malaria treatment, possible misuse of anti-malarial drugs, and an increased potential for drug resistance. METHODS: The spatial patterns of treatment-seeking practices were first examined using hot-spot analysis (Local Getis-Ord Gi statistic) and then modelled using regression. Ordinary least squares (OLS) regression identified key factors explaining more than 80% of the variation in control programme and vendor treatment preferences. Geographically weighted regression (GWR) was then used to assess where each factor was a strong predictor of treatment-seeking preferences. RESULTS: Several factors including tribal affiliation, housing materials, household densities, education levels, and proximity to the regional urban centre, were found to be effective predictors of malaria treatment-seeking preferences. The predictive strength of each of these factors, however, varied across the study area. While education, for example, was a strong predictor in some villages, it was less important for predicting treatment-seeking outcomes in other villages. CONCLUSION: Understanding where each factor is a strong predictor of treatment-seeking outcomes may help in planning targeted interventions aimed at increasing control programme usage. Suggested strategies include providing additional training for the Building Resources across Communities (BRAC) health workers, implementing educational programmes, and addressing economic factors.

Ensemble Models for Tick Vectors: Standard Surveys Compared with Convenience Samples.

Ensembles of Species Distribution Models (SDMs) represent the geographic ranges of pathogen vectors by combining alternative analytical approaches and merging information on vector occurrences with more extensive environmental data. Biased collection data impact SDMs, regardless of the target species, but no studies have compared the differences in the distributions predicted by the ensemble models when different sampling frameworks are used for the same species. We compared Ensemble SDMs for two important Ixodid tick vectors, Amblyomma americanum and Ixodes scapularis in mainland Florida, USA, when inputs were either convenience samples of ticks, or collections obtained using the standard protocols promulgated by the U.S. Centers for Disease Control and Prevention. The Ensemble SDMs for the convenience samples and standard surveys showed only a slight agreement (Kappa = 0.060, A. americanum; 0.053, I. scapularis). Convenience sample SDMs indicated A. americanum and I. scapularis should be absent from nearly one third (34.5% and 30.9%, respectively) of the state where standard surveys predicted the highest likelihood of occurrence. Ensemble models from standard surveys predicted 81.4% and 72.5% (A. americanum and I. scapularis) of convenience sample sites. Omission errors by standard survey SDMs of the convenience collections were associated almost exclusively with either adjacency to at least one SDM, or errors in geocoding algorithms that failed to correctly locate geographic locations of convenience samples. These errors emphasize commonly overlooked needs to explicitly evaluate and improve data quality for arthropod survey data that are applied to spatial models.

Temporal and Spatial Differences between Symptomatic and Asymptomatic Malaria Infections in the Chittagong Hill Districts, Bangladesh.

Mapping asymptomatic malaria infections, which contribute to the transmission reservoir, is important for elimination programs. This analysis compared the spatiotemporal patterns of symptomatic and asymptomatic Plasmodium falciparum malaria infections in a cohort study of ∼25,000 people living in a rural hypoendemic area of about 179 km2 in a small area of the Chittagong Hill Districts of Bangladesh. Asymptomatic infections were identified by active surveillance; symptomatic clinical cases presented for care. Infections were identified by a positive rapid diagnostic test and/or microscopy. Fifty-three subjects with asymptomatic P. falciparum infection were compared with 572 subjects with symptomatic P. falciparum between mid-October 2009 and mid-October 2012 with regard to seasonality, household location, and extent of spatial clustering. We found increased spatial clustering of symptomatic compared with asymptomatic infections, and the areas of high intensity were only sometimes overlapping. Symptomatic cases had a distinct seasonality, unlike asymptomatic infections, which were detected year-round. In a comparison of 42 symptomatic Plasmodium vivax and 777 symptomatic P. falciparum cases from mid-October 2009 through mid-March 2015, we found substantial spatial overlap in areas with high infection rates, but the areas with the greatest concentration of infection differed. Detection of both symptomatic P. falciparum and symptomatic P. vivax infections was greater during the May-to-October high season, although a greater proportion of P. falciparum cases occurred during the high season compared with P. vivax. These findings reinforce that passive malaria surveillance and treatment of symptomatic cases will not eliminate the asymptomatic reservoirs that occur distinctly in time and space.

Sex differences in the incidence and case fatality rates from hemorrhagic fever with renal syndrome in China, 2004-2008.

BACKGROUND: Differences between male and female individuals in response to infectious diseases are an overlooked global health problem. METHODS: The relationship between sex and disease outcome was examined in populations of patients with hemorrhagic fever with renal syndrome (HFRS) in mainland China, where most cases of hantavirus exposure occur. HFRS in China is diagnosed on the basis of symptoms and is confirmed with serological testing. The geographical distribution, incidence, and case fatality rates (CFRs) of HFRS in China were estimated and compared by patient sex and age. In a subset of patients with HFRS, clinical manifestations of HFRS were assessed using latent class analysis and compared by sex. RESULTS: There were 80,671 HFRS cases reported during the period 2004-2008, with a majority of HFRS cases (39.2%) occurring among individuals 20-39 years of age. The incidence of HFRS was higher among male patients than among female patients for all individuals >10 years of age. There were 945 deaths (CFR, 1.17%) due to HFRS in China during the period 2004-2008. CFRs were higher among women than among men between the ages of 20-39 and ≥ 50 years of age. There were no sex differences in the geographical distribution of HFRS cases or deaths. Although the prevalence of each clinical marker did not differ by sex, 2 profiles of clinical markers were identified that were related to both severity of disease and sex. CONCLUSIONS: These data illustrate a paradox in which the incidence of disease is greater for males, but the severity of disease outcome is worse for females. Several behavioral, societal, and biological factors are hypothesized to be involved.

Restricted enzooticity of hepatitis E virus genotypes 1 to 4 in the United States.

Hepatitis E is recognized as a zoonosis, and swine are known reservoirs, but how broadly enzootic its causative agent, hepatitis E virus (HEV), is remains controversial. To determine the prevalence of HEV infection in animals, a serological assay with capability to detect anti-HEV-antibody across a wide variety of animal species was devised. Recombinant antigens comprising truncated capsid proteins generated from HEV-subgenomic constructs that represent all four viral genotypes were used to capture anti-HEV in the test sample and as an analyte reporter. To facilitate development and validation of the assay, serum samples were assembled from blood donors (n = 372), acute hepatitis E patients (n = 94), five laboratory animals (rhesus monkey, pig, New Zealand rabbit, Wistar rat, and BALB/c mouse) immunized with HEV antigens, and four pigs experimentally infected with HEV. The assay was then applied to 4,936 sera collected from 35 genera of animals that were wild, feral, domesticated, or otherwise held captive in the United States. Test positivity was determined in 457 samples (9.3%). These originated from: bison (3/65, 4.6%), cattle (174/1,156, 15%), dogs (2/212, 0.9%), Norway rats (2/318, 0.6%), farmed swine (267/648, 41.2%), and feral swine (9/306, 2.9%). Only the porcine samples yielded the highest reactivities. HEV RNA was amplified from one farmed pig and two feral pigs and characterized by nucleotide sequencing to belong to genotype 3. HEV infected farmed swine primarily, and the role of other animals as reservoirs of its zoonotic spread appears to be limited.

Canaries in the coal mine: a cross-species analysis of the plurality of obesity epidemics.

A dramatic rise in obesity has occurred among humans within the last several decades. Little is known about whether similar increases in obesity have occurred in animals inhabiting human-influenced environments. We examined samples collectively consisting of over 20 000 animals from 24 populations (12 divided separately into males and females) of animals representing eight species living with or around humans in industrialized societies. In all populations, the estimated coefficient for the trend of body weight over time was positive (i.e. increasing). The probability of all trends being in the same direction by chance is 1.2 × 10(-7). Surprisingly, we find that over the past several decades, average mid-life body weights have risen among primates and rodents living in research colonies, as well as among feral rodents and domestic dogs and cats. The consistency of these findings among animals living in varying environments, suggests the intriguing possibility that the aetiology of increasing body weight may involve several as-of-yet unidentified and/or poorly understood factors (e.g. viral pathogens, epigenetic factors). This finding may eventually enhance the discovery and fuller elucidation of other factors that have contributed to the recent rise in obesity rates.

The role of age, ethnicity and environmental factors in modulating malaria risk in Rajasthali, Bangladesh.

BACKGROUND: Malaria is endemic in the Rajasthali region of the Chittagong Hill Tracts in Bangladesh and the Rajasthali region is the most endemic area of Bangladesh. Quantifying the role of environmental and socio-economic factors in the local spatial patterns of malaria endemicity can contribute to successful malaria control and elimination. This study aimed to investigate the role of environmental factors on malaria risk in Rajasthali and to quantify the geographical clustering in malaria risk unaccounted by these factors. METHOD: A total of 4,200 (78.9%; N = 5,322) households were targeted in Rajasthali in July, 2009, and 1,400 individuals were screened using a rapid diagnostic test (Falci-vax). These data were linked to environmental and socio-economic data in a geographical information system. To describe the association between environmental factors and malaria risk, a generalized linear mixed model approach was utilized. The study investigated the role of environmental factors on malaria risk by calculating their population-attributable fractions (PAF), and used residual semivariograms to quantify the geographical clustering in malaria risk unaccounted by these factors. RESULTS: Overall malaria prevalence was 11.7%. Out of 5,322 households, 44.12% households were living in areas with malaria prevalence of ≥ 10%. The results from statistical analysis showed that age, ethnicity, proximity to forest, household density, and elevation were significantly and positively correlated with the malaria risk and PAF estimation. The highest PAF of malaria prevalence was 47.7% for third tertile (n = 467) of forest cover, 17.6% for second tertile (n = 467) of forest cover and 19.9% for household density >1,000. CONCLUSION: Targeting of malaria health interventions at small spatial scales in Bangladesh should consider the social and socio-economic risk factors identified as well as alternative methods for improving equity of access to interventions across whole communities.

Data-model fusion to better understand emerging pathogens and improve infectious disease forecasting.

Ecologists worldwide are challenged to contribute solutions to urgent and pressing environmental problems by forecasting how populations, communities, and ecosystems will respond to global change. Rising to this challenge requires organizing ecological information derived from diverse sources and formally assimilating data with models of ecological processes. The study of infectious disease has depended on strategies for integrating patterns of observed disease incidence with mechanistic process models since John Snow first mapped cholera cases around a London water pump in 1854. Still, zoonotic and vector-borne diseases increasingly affect human populations, and methods used to successfully characterize directly transmitted diseases are often insufficient. We use four case studies to demonstrate that advances in disease forecasting require better understanding of zoonotic host and vector populations, as well of the dynamics that facilitate pathogen amplification and disease spillover into humans. In each case study, this goal is complicated by limited data, spatiotemporal variability in pathogen transmission and impact, and often, insufficient biological understanding. We present a conceptual framework for data-model fusion in infectious disease research that addresses these fundamental challenges using a hierarchical state-space structure to (1) integrate multiple data sources and spatial scales to inform latent parameters, (2) partition uncertainty in process and observation models, and (3) explicitly build upon existing ecological and epidemiological understanding. Given the constraints inherent in the study of infectious disease and the urgent need for progress, fusion of data and expertise via this type of conceptual framework should prove an indispensable tool.

Validating Species Distribution Models With Standardized Surveys for Ixodid Ticks in Mainland Florida.

Tick-borne pathogens are of growing concern. The U.S. Centers for Disease Control and Prevention (CDC) developed guidelines standardizing surveys of tick vectors to better monitor the changes in their occurrences. Unbiased surveillance data, from standardized surveys, are presumed critical to generate valid species distribution models (SDMs). We tested previously generated SDMs from standardized protocols for three medically important ticks [Amblyomma americanum (Linnaeus, Ixodida, Ixodidae), Ixodes scapularis (Say, Ixodida, Ixodidae), and Dermacentor variabilis (Say, Ixodida, Ixodidae)]. These previous models ruled out a quarter to half of the state as having these species, with consensus occurrence in about a quarter of the state. New surveys performed throughout 2019 on 250 transects at 43 sites indicated the rule-out functions were 100% accurate for I. scapularis and D. variabilis and 91.9% for A. americanum. As SDM concordance increased, the proportion of transects yielding ticks increased. Independent surveys of SDMs provide external validation-an aspect missing from many SDM studies.

Prevalence of Hantaviruses Harbored by Murid Rodents in Northwestern Ukraine and Discovery of a Novel Puumala Virus Strain.

In Europe, two species of hantaviruses, Puumala orthohantavirus (PUUV) and Dobrava orthohantavirus (DOBV), cause hemorrhagic fever with renal syndrome in humans. The rodent reservoirs for these viruses are common throughout Ukraine, and hence, the goal of this study was to identify the species and strains of hantaviruses circulating in this region. We conducted surveillance of small rodent populations in a rural region in northwestern Ukraine approximately 30 km from Poland. From the 424 small mammals captured, we identified nine species, of which the most abundant were Myodes glareolus, the bank vole (45%); Apodemus flavicollis, the yellow-necked mouse (29%); and Apodemus agrarius, the striped field mouse (14.6%) Using an indirect immunofluorescence assay, 15.7%, 20.5%, and 33.9% of the sera from M. glareolus, A. glareolus, and A. flavicollis were positive for hantaviral antibodies, respectively. Additionally, we detected antibodies to the hantaviral antigen in one Microtus arvalis, one Mus musculus, and one Sorex minutus. We screened the lung tissue for hantaviral RNA using next-generation sequencing and identified PUUV sequences in 25 small mammals, including 23 M. glareolus, 1 M. musculus, and 1 A. flavicollis, but we were unable to detect DOBV sequences in any of our A. agrarius specimens. The percent identity matrix and Bayesian phylogenetic analyses of the S-segment of PUUV from 14 M. glareolus lungs suggest the highest similarity (92-95% nucleotide or 99-100% amino acid) with the Latvian lineage. This new genetic information will contribute to future molecular surveillance of human cases in Ukraine.

Modelling distributions of Aedes aegypti and Aedes albopictus using climate, host density and interspecies competition.

Florida faces the challenge of repeated introduction and autochthonous transmission of arboviruses transmitted by Aedes aegypti and Aedes albopictus. Empirically-based predictive models of the spatial distribution of these species would aid surveillance and vector control efforts. To predict the occurrence and abundance of these species, we fit a mixed-effects zero-inflated negative binomial regression to a mosquito surveillance dataset with records from more than 200,000 trap days, representative of 53% of the land area and ranging from 2004 to 2018 in Florida. We found an asymmetrical competitive interaction between adult populations of Aedes aegypti and Aedes albopictus for the sampled sites. Wind speed was negatively associated with the occurrence and abundance of both vectors. Our model predictions show high accuracy (72.9% to 94.5%) in validation tests leaving out a random 10% subset of sites and data since 2017, suggesting a potential for predicting the distribution of the two Aedes vectors.

Progress and challenges to control malaria in a remote area of Chittagong hill tracts, Bangladesh.

BACKGROUND: Malaria is endemic in 13 eastern districts where the overall infection prevalence is 3.97%. In 2006, Bangladesh received US$ 36.9 million from the Global Fund to Fight AIDS, Tuberculosis and Malaria (GFATM) to support the national malaria control programme of Bangladesh. OBJECTIVES: The objective of this study was to i) clarify factors associated with treatment seeking behaviours of malaria ii) distribution of LLIN, and iii) re-treatment of ITN in remote area of a CHT district of Bangladesh two years after implementation of national control programme. METHODS: All households of Rajasthali sub-district of Rangamati district (households about 5,322, population about 24,097), all BRAC health workers (n = 15), health facilities and drug vendors' locations were mapped. Distances from households to health facilities, BRAC health workers and drug vendors were calculated. Logistic regression analysis was performed to assess the associations between the choice of the treatment and the distance to various treatment sources, education, occupation and ethnicity. SaTScan was used to detect clustering of treatment-seeking approaches. FINDINGS: LLIN distribution and the re-treatment of ITN exceeded target goals. The most common treatment facility for malaria-associated fever was malaria control programme led by BRAC and government (66.6%) followed by the drug vendor (48.8%). CONCLUSION: Closeness to health facilities run by the malaria control programme and drug vendors were significantly associated with the choice of treatment. A high proportion of people preferred drug vendors without having a proper diagnosis. Drug vendors are highly patronized and thus there is a need to improve their services for public health good. Otherwise it may cause incomplete treatment, misuse of anti-malarial drugs that will contribute to the risk of drug resistance and jeopardize the present malaria control efforts in Bangladesh.